Hello guys, if you want to learn about Microservices architecture and how to create Microservices with Java using Spring Boot and Spring cloud framework and looking for the best online courses then you have come to the right place. Earlier, I have shared the best free Microservices courses for Java programmers and in this article, I am going to share the best online courses to learn Microservices with Java in 2025. Popularity of Cloud Computing has given an exponential rise to Microservices architecture because they go hand in hand.  --- Java Interview questions and tutorials

There is no doubt that JavaScript is the #1 Programming language in the world and Node.js is one of the biggest reasons for that. Initially, JavaScript was considered just a client-side scripting language but Node.js has changed all that by allowing developers to create dynamic web pages on the server-side using JavaScript. It is also rated as the most popular framework on the StackOverflow Developers survey. The most important benefit of Node.js is that it allows you to build a full-stack application based on just one language, JavaScript. This is especially useful for start-ups that put a lot of emphasis on being able to iterate early and often. --- Java, Unix, Tibco RV and FIX Protocol Tutorial

My favorite Udemy courses to learn building AI Agents for production AI Agents are no longer science fiction — they’re the future of software development, and that future is now. In 2025, companies are racing to build autonomous AI systems that can research, analyze, make decisions, and execute tasks without human intervention. From AI sales representatives to automated research assistants, AI agents are transforming how businesses operate. But here’s the challenge: building production-grade AI agents requires more than just knowing how to call an API. You need to understand agent architectures, tool integration, multi-agent collaboration, RAG systems, and deployment at scale. I’ve spent the last three months exploring every major AI agent #course on Udemy, and I’m excited to share the 7 courses that will take you from zero to building production-ready AI agents. These aren’t just theoretical courses — you’ll build real applications using the latest frameworks like LangGraph, CrewAI, AutoGen, and OpenAI Agents SDK. Whether you’re a developer looking to add AI to your skillset, a founder building AI products, or an engineer at a company adopting AI agents, these courses will give you the practical knowledge to ship production-grade solutions. By the way, if you are in hurry and just want to start, you can go and join The Complete Agentic AI Engineering Course (2025) on Udemy. It’s my favorite and one of the best Udemy course to learn building AI Agents for production. Why AI Agents Are the Most Important Skill in 2026? Before we dive into the courses, let’s understand why AI agents matter: 1. AI Agents Are the Next Paradigm Shift * Moving from prompt → response to autonomous task execution * Agents can break down complex problems and solve them independently * Multi-agent systems can collaborate like human teams 2. Massive Market Demand * Companies are urgently hiring AI agent engineers * Average AI engineer salary: $150,000-$250,000+ in US * Startups raising millions to build agentic AI solutions * Every major tech company is investing in agent technologies 3. Real Business Applications * Customer service agents (replacing traditional chatbots) * Sales development representatives (SDRs) * Research and analysis automation * Code generation and review * Data analysis and insights * Content creation and editing * Process automation across industries 4. Cutting-Edge Technology * OpenAI Agents SDK, Claude Computer Use, Gemini agents * LangGraph for complex agent workflows * CrewAI for multi-agent collaboration * AutoGen from Microsoft Research * Model Context Protocol (MCP) for agent-computer interaction Now, let’s explore the courses that will make you an AI agent expert. 7 Best Udemy Courses for Building AI Agents in 2026 Without any further ado, here are the best Udemy courses you can join to learn how to build AI agents which can survive test of time in production 1. The Complete Agentic AI Engineering Course (2025) Students: 141,746 Rating: 4.7/5 (19,102 ratings) Level: Beginner to Advanced This is THE most comprehensive AI agents course on Udemy. If you can only take one course, make it this one. What You’ll Learn: * 8 Production Projects: Career Digital Twin, SDR Agent, Deep Research Agent, Stock Picker, and more * OpenAI Agents SDK: Master OpenAI’s official framework for building agents * CrewAI: Build collaborative multi-agent systems * LangGraph: Create complex agent workflows and state machines * AutoGen: Microsoft’s framework for conversational agents * Model Context Protocol (MCP): Enable agents to interact with computers * Deployment: Ship your agents to production * Real-world applications: Build agents that solve actual business problems Why This Course Stands Out: The instructor takes you from zero to building eight production-ready AI agents in just 30 days. These aren’t toy projects — they’re applications you could launch as SaaS products tomorrow. Project 1: Career Digital Twin teaches you to build an AI agent that represents you to employers. This alone could land you a job by demonstrating your AI skills in the interview process. Project 2: SDR Agent shows you how to build an AI sales representative that crafts and sends professional emails. This is an instant business application — companies pay thousands monthly for SDR services. Project 3: Deep Research Agent is the killer project. You’ll build a multi-agent system that conducts comprehensive research on any topic, similar to how Perplexity or ChatGPT with search works. What impressed me most was the coverage of the latest frameworks. While other courses teach outdated patterns, this course uses OpenAI’s brand-new Agents SDK (released late 2024) and the latest versions of LangGraph and CrewAI. Perfect For: * Developers wanting comprehensive AI agent training * Entrepreneurs building AI-powered products * Engineers at companies adopting AI agents * Anyone serious about becoming an AI agent expert * People who learn best by building real projects Key Takeaway: By the end of this course, you’ll have eight portfolio projects and the skills to build production AI agents with any framework. This is the foundation every AI agent engineer needs. Pro Tip: Start with this course’s fundamentals, then use the specialized courses below to deep-dive into specific frameworks or use cases. Here is the link to join this course — The Complete Agentic AI Engineering Course (2025) 2. AI in Production: Gen AI and Agentic AI at Scale Students: 9,456 Rating: 4.8/5 (656 ratings) Duration: 18.5 hours Level: Intermediate to Advanced Building AI agents is one thing. Deploying them at scale to millions of users is entirely different. This course bridges that gap. What You’ll Learn: * Cloud Deployment: Deploy to AWS, GCP, Azure, and Vercel * MLOps: CI/CD for AI applications using Terraform and GitHub Actions * Amazon Bedrock: Use AWS’s managed LLM service * SageMaker: Deploy custom models at scale * RAG at Scale: Build retrieval-augmented generation systems that perform * Agent Deployment: Ship multi-agent systems to production * MCP Integration: Model Context Protocol for production agents * Observability: Monitor and debug AI systems in production * Security: Implement authentication, authorization, and data protection * Architecture: Design scalable, resilient AI infrastructures Why This Course Is Essential: Most AI courses teach you to build demos that run on your laptop. This course teaches you to build production systems that serve millions of users reliably. You’ll learn cloud architecture patterns specifically for AI applications — how to handle bursty traffic, manage LLM costs, implement caching strategies, and ensure your agents don’t hallucinate in production. The instructor covers all major cloud providers, so whether your company uses AWS, Azure, or GCP, you’re covered. The Terraform and GitHub Actions sections are particularly valuable — you’ll implement infrastructure-as-code and continuous deployment for AI apps. What sets this course apart is the focus on production concerns: latency, cost optimization, error handling, monitoring, and security. These are the skills that separate junior AI engineers from senior ones. Perfect For: * AI engineers deploying to production * DevOps engineers working with AI teams * CTOs/architects designing AI infrastructure * Engineers at companies scaling AI applications * Anyone building commercial AI products Key Takeaway: Building an AI agent that works on your laptop is impressive. Building one that serves 10 million users reliably at reasonable cost? That’s career-defining. This course teaches you how. Must-Know: This course assumes you understand AI basics. Pair it with Course #1 for complete coverage from development to deployment. Here is the link to join this course — AI in Production: Gen AI and Agentic AI at Scale 3. Master LLM Engineering & AI Agents: Build 14 Projects Students: 5,752 Rating: 4.6/5 (383 ratings) Level: Beginner to Advanced If you want project-based learning, this course delivers 14 complete AI agent projects. It’s like a coding bootcamp compressed into one course. What You’ll Learn: * 14 Complete Projects: Each teaching different agent patterns and use cases * Hugging Face: Work with open-source models * LangGraph: Master state-based agent workflows * CrewAI: Build collaborative agent teams * AutoGen: Conversational multi-agent systems * N8N: No-code agent automation * RAG Systems: Retrieval-augmented generation for agents * MCP: Model Context Protocol integration * OpenAI Agents SDK: Official OpenAI framework * LLM Foundations: How LLMs are trained, fine-tuned, and deployed Why This Course Excels: The 14-project structure means you’re constantly building, not just watching theory. Each project introduces new concepts and frameworks, so you gain breadth across the entire AI agent ecosystem. What I loved about this course was the progression. Early projects teach fundamentals, middle projects introduce complex patterns, and final projects combine everything into production-ready applications. The instructor also covers multiple frameworks (LangGraph, CrewAI, AutoGen, N8N), so you’re not locked into one tool. This flexibility is crucial because the AI landscape evolves rapidly — what’s popular today might be replaced tomorrow. The community aspect is fantastic. You get expert help when stuck and access to an AI community where students share projects and collaborate. Perfect For: * Developers who learn by building * People wanting broad exposure to AI frameworks * Bootcamp-style learners * Engineers building diverse AI applications * Anyone wanting 14 portfolio projects Key Takeaway: By the end, you’ll have 14 complete AI agent projects showcasing different frameworks, patterns, and use cases. This diversity makes you more versatile and hireable. Pro Tip: Build your own versions of each project with modifications. Employers care about what you can build, not just courses you’ve completed. Here is the link to join this course — Master LLM Engineering & AI Agents: Build 14 Projects 4. Learn Agentic AI — Build Multi-Agent Automation Workflows Students: 9,653 Rating: 4.6/5 (798 ratings) Duration: 10 hours Level: Intermediate This course specializes in multi-agent systems using Microsoft’s AutoGen framework. If you’re building complex workflows where multiple agents collaborate, this is your deep dive. What You’ll Learn: * AutoGen Framework: Microsoft’s multi-agent system * Agent Collaboration: How agents work together to solve problems * Specialized Agents: Jira Agent for bugs, Playwright Agent for browser automation, API Agent for testing, DB Agent for data analysis * MCP Integration: Model Context Protocol for agent-computer interaction * Workflow Orchestration: Coordinate multiple agents effectively * Self-Correction: Build agents that improve their own outputs * Autonomous Execution: Agents that work without constant supervision * Real-World Automation: Practical business use cases Why This Course Is Unique: AutoGen is one of the most powerful frameworks for building multi-agent systems, but it’s also one of the most complex. This course makes it accessible. The specialized agent examples are incredibly practical. The Jira Agent that analyzes bugs automatically? That’s a real tool teams would pay for. The Playwright Agent that automates browser tasks? That’s replacing manual QA work. What impressed me was the focus on agent collaboration patterns. You’ll learn how to design systems where agents communicate, delegate tasks, and verify each other’s work — just like human teams. The course also covers self-correction and autonomous execution, which are crucial for production agents. Your agents need to handle errors gracefully and iterate toward better solutions without breaking. Perfect For: * Engineers building complex automation workflows * Teams adopting multi-agent architectures * Developers interested in AutoGen specifically * Anyone automating repetitive business processes * QA engineers exploring AI-powered testing Key Takeaway: Multi-agent systems are more powerful than single agents but also more complex. This course teaches you to orchestrate multiple specialized agents that collaborate effectively. Must-Know: AutoGen has a steeper learning curve than CrewAI or LangGraph. This course makes it digestible, but expect to spend time experimenting. Here is the link to join this course — Learn Agentic AI — Build Multi-Agent Automation Workflows 5. LangChain — Develop AI Agents with LangChain & LangGraph Students: 132,571 Rating: 4.6/5 (38,816 ratings) Level: Beginner to Advanced LangChain is the most popular framework for building LLM applications, and LangGraph extends it for complex agent workflows. This is the definitive course on both. What You’ll Learn: * LangChain Fundamentals: Chains, prompts, memory, and tools * LangGraph: State machines and complex agent workflows * Agent Architectures: ReAct, Chain of Thought, Few-Shot prompting * Tool Integration: Connect agents to APIs, databases, and services * Memory Systems: Give agents long-term and short-term memory * RAG Implementation: Retrieval-augmented generation * Production Patterns: Best practices for reliable agents * Prompt Engineering: Advanced techniques for agent behavior * Real-World Projects: End-to-end working agents Why This Course Dominates: With 132,571 students, this is the most popular AI agent course on Udemy for good reason. The instructor deeply understands LangChain and explains not just how to use it, but why it’s designed that way. The course covers LangChain 1.0+, which introduced significant changes from earlier versions. You’re learning the latest patterns, not outdated approaches. What sets this course apart is the focus on understanding underlying concepts. You’ll learn Chain of Thought reasoning, ReAct patterns, and Few-Shot prompting — the theoretical foundations that make agents work. This knowledge transfers to any framework, not just LangChain. The LangGraph section is particularly valuable. LangGraph enables complex agent workflows with branching, looping, and state management. It’s more powerful than simple chains but requires understanding state machines — this course explains it clearly. Perfect For: * Developers new to LangChain * Engineers building complex agent workflows * Anyone using LangGraph for production agents * Developers wanting to understand agent architectures deeply * Teams standardizing on LangChain Key Takeaway: LangChain and LangGraph are industry-standard tools. Mastering them makes you immediately valuable to companies building AI agents. Pro Tip: LangChain updates frequently. After this course, follow the official documentation and community to stay current with new features. Here is the link to join this course — LangChain — Develop AI Agents with LangChain & LangGraph 6. AI Agents & Workflows — The Practical Guide Students: 11,256 Rating: 4.6/5 (1,635 ratings) Level: Beginner to Intermediate This course focuses on practical applications — building agents that actually solve real business problems. If you’re more interested in use cases than frameworks, start here. What You’ll Learn: * AI Agent Fundamentals: What agents are and how they work * Workflow Automation: Use AI to automate complex processes * Multi-Agent Systems: Coordinate multiple agents * Tool Integration: Connect agents to external services * Use Case Examples: Customer service, research, data analysis, content creation * Agent vs. Workflow: When to use which approach * Production Deployment: Ship agents to real users * Practical Projects: Build agents for actual business needs Why This Course Is Valuable: Many courses teach frameworks but don’t explain when to use them. This course is all about practical application — understanding which problems agents solve and how to build solutions. The “Agent vs. Workflow” distinction is crucial. Not every problem needs a fully autonomous agent. Sometimes a well-designed workflow with AI components is better. This course teaches you to make that judgment call. The use cases are excellent. You’ll build customer service agents, research assistants, data analysts, and content creators. These are applications businesses actually need, not just demos. What I appreciated most was the focus on deployment. The instructor doesn’t just show you how to build agents — they show you how to ship them to production and handle real user interactions. Perfect For: * Non-technical founders building AI products * Product managers designing AI features * Developers new to AI who want practical skills fast * Business analysts exploring AI automation * Anyone wanting quick wins with AI agents Key Takeaway: You don’t need to master every framework to build valuable AI agents. Understanding use cases and choosing the right tools for each problem is more important. Pro Tip: After this course, you’ll know which problems agents can solve. Then deep-dive into specific frameworks (LangGraph, CrewAI, etc.) based on your needs. Here is the link to join this course — AI Agents & Workflows — The Practical Guide 7. AI Agents Crash Course: Build with Python & OpenAI Students: 2,202 Rating: 4.7/5 (127 ratings) Duration: 3.5 hours Level: Beginner If you’re short on time but want to understand AI agents quickly, this 3.5-hour crash course delivers maximum value in minimum time. What You’ll Learn: * OpenAI SDK: Build agents using OpenAI’s official tools * Python Fundamentals: AI agent development in Python * Tool Calling: Enable agents to use external tools * Memory Systems: Give agents context and history * Streaming Responses: Real-time agent outputs * Prompt Engineering: Control agent behavior effectively * Context Engineering: Provide relevant information to agents * RAG Implementation: Retrieval-augmented generation basics * Guardrails: Ensure agents behave safely and appropriately * AgentBuilder: Rapid agent prototyping Why This Course Works: In just 3.5 hours, you’ll go from zero to building functional AI agents. It’s not comprehensive, but it’s incredibly efficient. The focus on OpenAI’s SDK is smart because it’s the most accessible starting point. OpenAI provides the best-documented APIs and the most capable models (GPT-4, GPT-4-Turbo, GPT-4o). What impressed me was how much ground the course covers in such a short time. You learn tool calling, memory, streaming, RAG, and guardrails — all the essential components of production agents. The guardrails section is particularly important and often overlooked. Production agents need safety constraints to prevent harmful outputs or unintended actions. This course teaches you to implement them from day one. Perfect For: * Busy developers wanting quick AI agent skills * People evaluating whether to invest more time in AI agents * Beginners who want an overview before deep-diving * Developers preferring OpenAI’s ecosystem * Anyone needing functional agent knowledge fast Key Takeaway: You can build production-quality AI agents in just a few hours of focused learning. This course proves it and gives you the fundamentals to explore deeper. Pro Tip: Use this as your entry point. After completing it, you’ll know if you want to invest in comprehensive courses like #1 or #3. Here is the link to join this course — AI Agents Crash Course: Build with Python & OpenAI How to Choose Your AI Agent Learning Path? With seven excellent courses, how do you decide your journey? Here are my recommendations: Complete Beginner Path (Zero to Job-Ready): * Start: AI Agents Crash Course (3.5 hours — quick overview) * Then: The Complete Agentic AI Engineering Course (comprehensive training) * Finally: AI in Production (deployment at scale) Result: Production-ready AI agent engineer in 4–6 weeks Framework Specialist Path: * Start: LangChain & LangGraph (master the most popular framework) * Then: Learn Agentic AI with AutoGen (multi-agent systems) * Finally: The Complete Agentic AI Engineering Course (CrewAI and OpenAI Agents SDK) Result: Expert in multiple AI agent frameworks Project-Based Learning Path: * Start: Master LLM Engineering — 14 Projects (breadth through projects) * Then: The Complete Agentic AI Engineering Course (8 more production projects) Result: 22 portfolio projects demonstrating diverse AI agent skills Business/Practical Path (Non-Technical): * Start: AI Agents & Workflows — Practical Guide (use cases first) * Then: AI Agents Crash Course (technical basics) * Finally: The Complete Agentic AI Engineering Course (comprehensive skills) Result: Business understanding + technical capability Maximizing Your Udemy Learning Experience Here’s how to get the most value from these courses: 1. Get Udemy Personal Plan At around $20–30/month with a Udemy Personal Plan, you get access to 26,000+ courses. For AI engineers, this is invaluable because you’ll want to explore Python, cloud platforms, databases, and more. 2. Wait for Sales (Or Don’t) Udemy courses go on sale frequently (often $10–20). But honestly, even at full price ($20–40), these courses are worth it. Don’t let waiting for sales delay your learning. 3. Code Along, Don’t Just Watch Critical: Type every line of code yourself. Don’t copy-paste. The learning happens in debugging errors and understanding why code works. 4. Build Your Own Projects After each course section, build something different: * After learning CrewAI: Build a marketing team of agents * After learning RAG: Build a personal knowledge assistant * After learning AutoGen: Build a code review agent system 5. Join Course Communities Most courses have Q&A sections and Discord communities. Ask questions, share projects, and learn from other students. 6. Focus on One Framework Initially Don’t try to master LangGraph, CrewAI, AutoGen, and OpenAI Agents SDK simultaneously. Pick one, build 3–5 projects with it, then explore others. 7. Deploy Something to Production Theory is worthless without practice. Deploy at least one agent to production (even if it’s just for yourself). Use Vercel, Railway, or AWS free tiers. Common AI Agent Challenges These Courses Solve “I don’t understand the difference between agents and chatbots” Solved in: AI Agents & Workflows — The Practical Guide This course clearly distinguishes agents (autonomous systems that use tools and make decisions) from chatbots (conversational interfaces). “I can call OpenAI APIs but can’t build real agents” Solved in: The Complete Agentic AI Engineering Course, AI Agents Crash Course Both courses bridge the gap from API calls to autonomous agents with memory, tools, and complex workflows. “My agents work locally but crash in production” Solved in: AI in Production: Gen AI and Agentic AI at Scale Comprehensive production deployment, error handling, monitoring, and scaling strategies. “I can’t get multiple agents to collaborate effectively” Solved in: Learn Agentic AI with AutoGen, The Complete Agentic AI Engineering Course Both teach multi-agent orchestration, communication patterns, and collaborative problem-solving. “I don’t know which framework to use” Solved in: Master LLM Engineering — 14 Projects, The Complete Agentic AI Engineering Course Both expose you to multiple frameworks, letting you compare and choose based on your needs. “My agents hallucinate or give wrong answers” Solved in: LangChain & LangGraph, AI Agents Crash Course Both teach RAG, fact-checking, and guardrails to improve agent accuracy and safety. Is Udemy Worth It for AI Agent Learning? Let’s compare options: Udemy (All 7 Courses): ~$140–280 one-time (or $20–30/month with Personal Plan) AI Engineering Bootcamp: $8,000–20,000 University AI Course: $2,000–8,000 Private AI Tutoring: $100–200/hour Udemy Advantages: * Learn at your own pace * Lifetime access to course materials * 30-day money-back guarantee * Active Q&A communities * Constantly updated content * Multiple instructors/perspectives Udemy Disadvantages: * No formal credentials (but portfolios matter more) * Requires self-discipline * No job placement services * You need to create your own learning path My Take: For AI agents specifically, Udemy is unbeatable on value. The course quality is high, the instructors are practitioners, and the focus is on building real projects — not academic theory. Getting Started with AI Agents Today Ready to become an AI agent engineer? Here’s your action plan: Step 1: Choose Your Path Pick one of the learning paths I outlined based on your goals (beginner, framework specialist, project-based, or business-focused). Step 2: Get Access Sign up for Udemy and either buy individual courses or get the Personal Plan for access to everything. Step 3: Start Small Begin with AI Agents Crash Course (3.5 hours) to validate your interest before committing to longer courses. Step 4: Set a Schedule Block 1–2 hours daily for learning. Consistency beats intensity — daily practice compounds quickly. Step 5: Build Immediately After each course section, build something. Don’t wait until “finishing” the course to start building. Step 6: Share Your Work Post projects on GitHub, LinkedIn, and Twitter. The AI community is active and supportive — you’ll get feedback and opportunities. Frequently Asked Questions Q: Do I need a CS degree to take these courses? A: No. Basic programming knowledge (Python preferred) is enough. If you can write functions and loops, you can learn AI agents. Q: Which programming language should I know? A: Python. All AI agent frameworks use Python. If you don’t know Python, learn basics first, then return to these courses. Q: How long to become job-ready? A: If you code daily and build projects, 2–3 months to be job-ready for AI engineer roles. Focus on portfolio projects — employers hire based on what you can build. Q: Are these courses updated for 2025? A: Yes. All courses listed are updated for 2025 with the latest frameworks (OpenAI Agents SDK, LangGraph 1.0+, CrewAI, latest AutoGen). Q: Should I learn LangChain or CrewAI first? A: LangChain. It’s more widely adopted, better documented, and understanding it makes other frameworks easier to learn. Q: Can I build AI agents without GPT-4? A: Yes. You can use Claude, Gemini, or open-source models. However, GPT-4 is currently the most capable for agent tasks. Q: Do these courses cover deployment? A: Course #2 (AI in Production) is entirely about deployment. Course #1 also covers deployment basics. Final Thoughts: The AI Agent Revolution Is Now AI agents aren’t the future — they’re the present. Companies are building them now. Startups are raising millions for agentic AI products. The market is moving fast. These seven Udemy courses represent the best AI agent education available. The instructors are practitioners building real systems. The projects are production-ready. The skills are immediately applicable. Whether you’re a developer expanding your skillset, a founder building AI products, or an engineer at a company adopting AI, these courses will give you the practical knowledge to succeed.The question isn’t “Should I learn AI agents?” --- Top 7 Udemy Courses to Build Production-Grade AI Agents in 2026 was originally published in Javarevisited on Medium, where people are continuing the conversation by highlighting and responding to this story.

The Real Reason Most Engineers Fail System Design Interviews (Even Experienced Ones) credit — ByteByteGo Hello Guys, If you’ve ever prepared for a System Design Interview, you know the feeling — you’ve built large systems, written production code, maybe even led architecture discussions at work. Yet, when you sit down for the interview, everything suddenly feels different. The interviewer throws a vague prompt like “Design Rate Limiter”, “Design LRU Cache”, “Design Twitter” or “Design Uber,” and your mind goes blank. You’re not alone. Even senior engineers with years of experience often struggle to perform well in system design interviews. The truth is, success in these interviews has less to do with experience and more to do with structured thinking, communication, and understanding trade-offs at scale. After years of studying and helping others prepare for these interviews, I’ve realized most engineers fail for predictable reasons — and the good news is, they’re all fixable. 1. Real-World Experience ≠ Interview Readiness Many experienced engineers assume their day-to-day experience designing systems at work will automatically translate into interview success. Unfortunately, that’s rarely the case. In your job, you work within an existing system with well-defined constraints, known tech stacks, and team context.In an interview, you’re expected to design a system from scratch while thinking aloud, justifying trade-offs, and explaining design decisions clearly — all in under 45 minutes. That’s a completely different skill set, and one that needs deliberate practice. This is where structured resources like ByteByteGo come in. Founded by Alex Xu, author of the popular System Design Interview book series, ByteByteGo breaks down complex design topics into intuitive visuals, real-world examples, and step-by-step design frameworks. Their System Design Fundamentals and Case Study courses are designed to build that interview-ready mindset — and right now, they’re offering a 50% discount on their lifetime plan, which gives you access to all courses, diagrams, and system design updates forever. It’s easily the best long-term investment for serious interview prep and I highly recommend it to both senior and junior engineers who wants to grow and their career and aim for FAANG or Investment banking jobs as AVP or VP. Here is the link to get the discount — 50% discount on their lifetime plan 2. Lack of a Structured Framework Most engineers jump straight into designing the architecture without first clarifying the problem or constraints. This leads to messy answers and incomplete designs. Interviewers expect a structured approach — defining scope, identifying bottlenecks, estimating scale, and gradually evolving the system. Without a framework, even good ideas come across as chaotic. This is why I recommend resources like DesignGurus.io and Exponent for structured learning. * DesignGurus.io’s Grokking System Design course is one of the most popular system design resources on the internet. It teaches reusable design patterns and covers 20+ real-world systems like YouTube, Instagram, and WhatsApp. Grokking the System Design Interview | Video Course by Design Gurus * Exponent focuses on mock interviews and interactive learning, making it perfect for practicing your articulation and communication during interviews. Interview prep for product, engineering, data science, and more - Exponent Combine those with ByteByteGo’s visual explanations, and you’ll have a complete system design preparation toolkit. Here is an example of visual guide from ByteByteGo for designing a System like YouTube 3. Not Practicing End-to-End Design Reading books or watching videos is helpful, but practice is where the real learning happens. You need to simulate actual interviews — think aloud, make trade-offs, and explain why you choose one approach over another. Platforms like Codemia.io and System Design School do a fantastic job at providing realistic, scenario-based challenges. Here are few System Design question you can practice on Codemia.io for free, this will give you good idea of what it takes to solve such problems on real interview and whether you are ready or not * Codemia | Master System Design Interviews Through Active Practice * Master System Design Interviews Through Active Practice Codemia also offers guided practice problems and architecture case studies tailored for modern interviews, while System Design School helps you practice live and get expert feedback. Learn System Design and Ace Your System Design Interview | Learn from Ex-FAANG Engineers 4. Ignoring the Fundamentals Before diving into distributed systems and load balancers, you need to have a solid grasp of computer science fundamentals — caching, databases, consistency models, and concurrency. If these concepts aren’t clear, you’ll struggle to reason about system trade-offs. This is where Educative.io and AlgoMonster shine: * Educative’s Grokking the Modern System Design Interview and System Design Deep Dive: Real-World Distributed Systems courses are perfect for building core knowledge interactively. * Grokking System Design Interview: Patterns & Mock Interviews * System Design Deep Dive: Real-World Distributed Systems - AI-Powered Course AlgoMonster complements it by reinforcing your data structure and algorithmic thinking — essential when your design involves trade-offs between speed and space. 5. Overlooking Code Quality and Real-World Scenarios System design isn’t just about diagrams — it’s about writing robust, maintainable, and efficient systems. Many candidates overlook this aspect entirely. That’s where BugFree.ai can be a game-changer. It acts as your AI-powered code reviewer, catching bugs, bad patterns, and design flaws before they become interview embarrassments. Practicing with BugFree.ai improves not just your code but also your ability to reason about design trade-offs — a skill interviewers love to see. Here are popular classical system design questions you can practice on Bugfree.ai: * Design a URL Shortening Service like Bitly - System Design Interview Question * Design Parking Lot System - Object-Oriented Design Interview Question What Senior Engineers Can Do to Finally Crack the System Design Interview? If you’re a senior engineer, chances are you already understand distributed systems, APIs, and scaling — but the real challenge lies in communicating and structuring that knowledge under pressure. System Design Interviews are less about raw technical depth and more about demonstrating clear thinking, trade-off reasoning, and end-to-end system architecture design. Here’s what you can do to bridge that gap and ace your next interview: 1. Master the Framework, Not Just the Concepts Most engineers jump straight into designing databases or APIs without following a structured approach. Use proven frameworks such as ByteByteGo’s System Design Framework, which teaches you how to break problems into components like requirements, APIs, data modeling, storage, scalability, reliability, and trade-offs. Frameworks help you stay calm and methodical — which is exactly what interviewers look for. 👉 Check out ByteByteGo’s System Design Course (50% OFF Lifetime Plan) System Design · Coding · Behavioral · Machine Learning Interviews 2. Practice with Real Interview Scenarios Theory isn’t enough. You need exposure to actual interview-style problems like designing YouTube, WhatsApp, or Uber — under real time constraints. Platforms like DesignGurus.io and Codemia.io simulate real interview challenges, helping you refine your thinking and identify weak spots early. 👉 Join DesignGurus.io for real-world system design practice 👉 Join Codemia.io for structured interview prep and feedback Master System Design Interviews Through Active Practice 3. Learn by Watching Experts Design Seeing how top engineers approach problems can accelerate your learning curve. Exponent provides mock interviews and detailed walkthroughs of FAANG-style system design problems, helping you understand how experts think out loud, manage ambiguity, and communicate trade-offs effectively. 👉 Explore Exponent’s mock system design interviews Interview prep for product, engineering, data science, and more - Exponent 4. Build and Analyze Real Systems You’ll learn much faster by building actual systems — whether it’s a small-scale distributed cache or an event-driven notification service. Educative.io’s Grokking the System Design Interview and BugFree.ai both offer hands-on challenges where you can apply theory to real-world scenarios. 👉 Learn System Design interactively on Educative.io 👉 Use BugFree.ai for AI-assisted interview prep 5. Don’t Just Memorize — Internalize Trade-offs Senior engineers are expected to reason through design choices — not just recall patterns. Learn to explain why you chose Kafka over RabbitMQ, when to use SQL vs NoSQL, or how caching strategies affect consistency. Understanding trade-offs is what separates a mid-level engineer from a staff-level one. 6. Combine Practice + Feedback + Frameworks If you combine ByteByteGo’s structured explanations, DesignGurus.io’s hands-on problems, Exponent’s mock interviews, and Codemia.io’s guided approach — you’ll have the most complete toolkit to succeed. Add consistent weekly practice, and you’ll notice a huge improvement in confidence and clarity. Why ByteByteGo Is Still the Best Resource in 2025 There are dozens of great platforms for system design prep today, but ByteByteGo remains the gold standard — and for good reason. Here’s why it stands out: * Visual learning — Every concept is illustrated with diagrams that make even complex systems easy to understand. * Real-world case studies — From Netflix to Dropbox, you’ll see how top-tier companies actually design their systems. * Lifetime access — A one-time payment gives you lifetime access to all current and future content. * 50% discount offer — Their lifetime plan is currently half off, making it an unbeatable value for the depth and quality of material you get. If you’re serious about cracking system design interviews — or even improving as an engineer — ByteByteGo should be your first stop. 👉 Grab ByteByteGo’s Lifetime Plan at 50% OFF and start learning System Design the visual way — faster, deeper, and smarter. Final Thoughts System Design Interviews are hard, but not impossible. Most people fail because they rely on experience alone or jump in without structure. The right mindset, framework, and resources can make all the difference. Here’s a quick roadmap to prepare effectively: * Start with Educative or DesignGurus to learn the basics. * Move to ByteByteGo for visual explanations and deep dives. * Practice mock interviews on Exponent or Codemia.io. * Use BugFree.ai for code review and architectural validation. * Finally, review case studies from System Design School to refine your storytelling and clarity. Passing the system design interview isn’t about luck or memorizing patterns — it’s about building intuition. Once you master that, even the toughest design questions start to feel natural. Other #Programming and Interview Articles you may like * ByteByteGo vs LeetCode? which one is better for tech interview? * How Algomonster helped me to master DSA for interviews? * Exponent 70% OFF — Is It Worth It for FAANG Interview Prep? * LeetCode vs. AlgoMonster? Which One Should You Use for Coding Interviews? * ByteByteGo Lifetime Plan Review: Is It the Best Investment for Developers in 2025? * 25 Software Design Interview Questions for Programmers * ByteByteGo vs NeetCode vs Educative? which one is better? * Codemia.io Annual vs. Lifetime Plan? * Is ByteByteGo a good place for Coding interviews? * 3 Free Books and Courses for System Design Interviews * Is System Design Interview RoadMap by DesignGuru worth it? * Why System Design Is the Hardest Part of FAANG Interviews? * How to Prepare for Coding Interviews? * AlgoMonster vs Exponent vs DesignGurus? * Codemia.io 65% OFF Lifetime Plan — Is It Worth It for FAANG Interview? * Is DesignGuru’s System Design Course worth it * Algomonster Review 2025 — Is it worth it? * Is Exponent’s System Design Course worth it? * LeetCode vs AlgoMonster? Which is better for Coding Interview? * 10 Best Places to Learn System Design in 2025 * My Favorite Software Design Courses for 2025 * ByteByteGo 50% OFF? Should you Join? * 10 Reasons to Learn System Design in 2025 Thanks for reading this article so far. If you like this article then please share them with your friends and colleagues. If you have any questions or feedback, then please drop a note.P. S. — If you just want to do one thing at this moment, go join ByteByteGo and start learning System Design and Coding Interview concepts, you will thank me later. The FAANG dream job you always wanted is not far anymore. System Design · Coding · Behavioral · Machine Learning Interviews --- Why Even Senior Engineers Struggle to Pass the System Design Interview? was originally published in Javarevisited on Medium, where people are continuing the conversation by highlighting and responding to this story.

Hello guys, you might know that a massive chunk of a developer's time is wasted in trying to repeat tasks and commands, especially when it comes to working with a bunch of UNIX or Linux machines, and a good knowledge of shell scripting can free you from such mundane task and give time to do some interesting stuff. If you don't know what shell scripting is then let me tell you is nothing but a program written using shell built-ins, and Linux commands to automate things, like checking if a host is reachable or finding and deleting large files that are older than certain days or archiving them into another machine. --- Java, Unix, Tibco RV and FIX Protocol Tutorial

A detailed comparison of AlgoMonster, Exponent, and DesignGurus to help you choose the right coding interview prep platform in 2025 Hello guys, when you’re preparing for FAANG-level coding interviews in 2025, the platform you choose matters. It’s not just about having access to problems; it’s about structure, feedback, teaching clarity, community, and scalability. Three names that frequently come up are AlgoMonster, Exponent, and DesignGurus. Each has its strengths and trade-offs. In this article, I’ll compare them across multiple dimensions and help you decide which fits your style and goals best. Why This Comparison Matters? Coding interview prep is no longer just about grinding 1000+ LeetCode problems. Interviewers expect you to: * Recognize patterns quickly (sliding window, two pointers, DP, graphs, etc.) * Handle novel combinations of patterns * Write clean, bug-free code under time pressure * Explain your trade-offs clearly * Recover gracefully from mistakes or follow-up changes So the question is: which platform gives you the best environment to build those muscles? Overview: What Each Platform Brings to the Table Now, let’s do a quick review of what each platform offer and bring to the table when it comes to coding interview prep in 2025: AlgoMonster * Strengths: Very structured curriculum, pattern-first approach, visual flowcharts, integrated IDE & AI help. * Weaknesses / Gaps: Less brand recognition compared to Exponent; mainly focused on coding, fewer mock interviews. * Best For: Developers who prefer guided learning and pattern mastery. Exponent * Strengths: Mock interviews, coaching, interview strategy, video-driven content, strong community. * Weaknesses / Gaps: Can be expensive; coding practice isn’t as deep as dedicated coding platforms. * Best For: Candidates who want holistic prep, including mocks, behavioral practice, and systems thinking. DesignGurus * Strengths: Clean “Grokking-style” pattern courses, focused on clarity and conciseness. * Weaknesses / Gaps: Less interactivity, fewer AI-driven features, fewer mock interview options. * Best For: Learners who prefer reading + examples and want a lean, pattern-based approach. Let’s break down how they compare across critical dimensions but before that here is a nice cheat sheet of coding patterns from DesignGurus.io Curriculum & Structure Each platform brings a different style of learning: AlgoMonster * Uses a pattern-based curriculum. You learn a pattern, then solve many problems built around it. * Offers flowcharts, visual guides, and “speedrun” modes to reinforce patterns. * Emphasizes ROI-driven topics, focusing first on patterns that appear most often in interviews. This makes it very good for people who want to avoid random problem lists and instead follow a more predictable path. Exponent * Less about raw coding depth; more about interview strategy, behavioral prep, mocks, system design frameworks. * Has video walkthroughs, lessons, coaching modules in addition to question banks. * Also includes company-specific guides and a community for interaction. This makes it better suited for holistic interview prep — not just coding. DesignGurus * Follows the “Grokking-style” approach: pattern + walkthroughs. Many of their courses focus on system design and coding patterns. * Content is concise, to the point; doesn’t overcomplicate. * Less emphasis on interactive tooling or AI feedback; more on clarity and examples. For learners who prefer digestible content and structured examples, DesignGurus is a good fit. They also provide System Design and coding interview templates like that for a structured response while answering system design questions on coding interviews. Practice & Feedback One of the biggest differentiators: how much feedback and interactivity do you get when you submit your code? AlgoMonster * You code inside their environment with built-in feedback. * They guide you through debugging, explanations, and pattern recognition. * Pattern-based repetition helps surface edge cases you might miss with random grinding. Exponent * Strong in mock interviews and expert coaching. Many users cite that the mocks were critical to improving their interview performance. * Allows peer interviews, community feedback, and structured coaching. * Less focus on built-in coding feedback or interactive error detection — users often complement with other platforms. DesignGurus * Primarily gives you solutions and explanations rather than real-time code feedback. * You learn by comparing your code with expert patterns. Thus, if you prefer hands-on iterative feedback, AlgoMonster excels; Exponent is strong when paired with mocks; DesignGurus is more for self-driven learners. Depth & Coverage AlgoMonster * Covers all major patterns: DFS, BFS, two pointers, graphs, DP, etc. * Also provides company-specific interview guides (Amazon, Google, etc.). Exponent * Covers technical + behavioral + system design interview topics * Usually not as deep in raw algorithm practice. Their focus is breadth over depth. DesignGurus * Strong in pattern coverage and clarity * Not always as deep in corner cases or variant problems as a hands-on platform Price & ROI You’ll often pay not just for content, but for time saved, feedback, and confidence. Here’s how they compare: * AlgoMonster: mid-tier pricing for what you get (pattern-first approach + feedback). Several reviewers consider it more affordable than many competitors. * Exponent: tends to be costlier, especially for coaching + mock interview add-ons. But some users say it’s “the best money spent” for interview prep. * DesignGurus: typically has lower or moderate pricing, especially for pattern courses. Good ROI if you don’t need heavy tooling or mocks. If you’re budget-conscious but want smart coverage and feedback, AlgoMonster often gives you the best middle ground. By the way, Algomonster is offering 50% discount now for a limited time. If you’re a long-term learner, mentor, or planning to revisit interviews every 1–2 years, the Pro Lifetime at $459 is 100% worth it — especially with the included coaching. You can also learn more about AlgoMonster plan here Strengths by Use Case If you want structured, pattern-first algorithm mastery → Pick AlgoMonster * Why: Strong feedback loop, built-in IDE, and curated progression that ensures you cover everything. If you want real mock interviews, coaching, and holistic prep → Pick Exponent * Why: Combines expert feedback with interview strategy, behavioral prep, and system design practice. If you want lean, example-based learning → Pick DesignGurus * Why: Clear, concise explanations of patterns that are cost-effective and quick to absorb. 💡 Pro Tip: You don’t have to stick to just one platform. Many learners use DesignGurus or AlgoMonster for algorithm practice, and then rely on Exponent for mock interviews and strategy coaching before their real interviews. Real Feedback & Community Sentiment * Users on Reddit and forums often praise AlgoMonster for its clean, pattern-based curriculum and say it feels faster and more structured than random LeetCode grinding. * Exponent mock interview reviews are frequently cited as game-changers for interview performance. * DesignGurus has loyal users who prefer its clarity over flashy features. Its discount promos often attract developers diving in. Which One Should You Choose in 2025? To decide, ask yourself: * How much feedback do you need? If you struggle with debugging or understanding mistakes, AlgoMonster’s feedback is huge. * Are mocks and coaching critical for you? If yes, Exponent is nearly unmatched in that area. * Do you prefer reading/diagrams over interactive tools? Then DesignGurus might feel more comfortable and less overwhelming. * Budget vs ambition If you want high ROI for coding practice, AlgoMonster is great. If you want full interview readiness with coaching, Exponent is worth the premium. * Mix & match You don’t have to pick just one. Many users use AlgoMonster or DesignGurus for algorithm practice and combine with Exponent for mocks and interview coaching. Final Verdict There’s no one-size-fits-all best, but here’s the summarized insight: * AlgoMonster is the best all-rounder for coding interview prep, especially if you’re focused on algorithms, want active feedback, and prefer a structured path. * Exponent is ideal as a complement — especially for mock interviews, strategy, and polishing your interview delivery. * DesignGurus shines when you prefer clarity, pattern-based learning, and lean content without extra fluff. If I were prepping for FAANG in 2025, I’d anchor my algorithm practice in AlgoMonster, then layer on Exponent mocks as I approach interview season. Use DesignGurus as a clarity aid or alternative learning path when I want fresh perspective. Other #Programming and Interview Articles you may like * 20+ array-based Problems for interviews * How Algomonster helped me to master DSA for interviews? * 10 Best Courses to Learn System Design for Interviews * 7 Best Courses to Learn Data Structure and Algorithms * 25 Software Design Interview Questions for Programmers * How to Prepare for Coding Interviews? * 16 Best Resources for System Design Interview Prep * Is DesignGuru’s System Design Course worth it * Algomonster Review 2025 — Is it worth it? * ByteByteGo vs NeetCode vs Educative? which one is better? * Is ByteByteGo a good place for Coding interviews? * 3 Free Books and Courses for System Design Interviews * Is System Design Interview RoadMap by DesignGuru worth it? * Is Exponent’s System Design Course worth it? * 10 Best Places to Learn System Design in 2025 * My Favorite Software Design Courses for 2025 * ByteByteGo 50% OFF? Should you Join? * 10 Reasons to Learn System Design in 2025 * 100+ Coding Problems to Crack Your Coding Interview Thanks for reading this article so far. If you like this article then please share them with your friends and colleagues. If you have any questions or feedback, then please drop a note.P. S. — If you are serious about getting into FAANG companies and want to leave no stone unturned then I also suggest you to join Algomonster for DSA and DesignGurus.io for System Design, and start practicing mock interviews on Exponent. This is the perfect recipe to crack coding interviews in quick time Tech Interview Preparation - System Design, Coding & Behavioral Courses | Design Gurus --- AlgoMonster vs Exponent vs DesignGurus? Which is Best for Coding Interview Prep in 2025? was originally published in Javarevisited on Medium, where people are continuing the conversation by highlighting and responding to this story.

Hello guys, how are you doing? Are you on track to accomplish your goals this year? I am sure you had made goals when this year was started, but if not, you can still check out 10 Things Java developers can learn in 2025. It's never too late. From my experience with interacting with many software developers, it seems DevOps, Docker, Kubernetes and Cloud Computing is the top priority for many programmers this year, especially senior Java developers. I have been receiving a lot of queries, emails, and chats about how to learn Docker and Kubernetes, two of the most popular DevOps tools. When it comes to learning, nothing beats personal training, but that's not always feasible; hence we need to rely on self-learning using books and online courses, and that's what I will suggest to you in this article. --- Java, Unix, Tibco RV and FIX Protocol Tutorial

The current 50% Discount on ByteByteGo lifetime plan is the best investment you can do for your career.

Hello Java programmers, if you want to learn Microservice architecture and look for free Microservice resources like free online courses, you have come to the right place. Earlier, I have shared the best Microservice courses for Java programmers to build Microservice using Java and the Spring framework, and today, I will share some free courses to learn Microservice in Java using Spring Boot and the Spring Cloud framework. If you don't know, Microservices is a modern architecture that goes along nicely with cloud computing and makes deployment, scaling, and even development easier.  --- Java Interview questions and tutorials

I’ve Read 20+ #Books on #AI and #LLM — Here Are My Top 5 Recommendations for 2026 My favorite books to learn AI and LLM Engineering in 2026 Hello guys, I’ve spent the past two years diving deep into the world of Artificial Intelligence and Large Language Models (LLMs). From engineering systems that scale to understanding model internals and prompt optimization, I’ve gone through more than 20 books to truly grasp the fast-evolving AI landscape. Some were theoretical, others highly practical, but only a few stood out as must-reads for anyone serious about building, deploying, or understanding AI systems in 2025. If you’re an AI engineer, developer, researcher, or even an ambitious learner wanting to understand the shift toward LLM-driven applications, this list will save you countless hours of exploration. These five books offer both the depth and practicality needed to navigate today’s AI ecosystem — from foundational understanding to hands-on implementation. 1. The LLM Engineering Handbook — Paul Iusztin & Maxime Labonne This book is arguably the best hands-on resource for anyone who wants to build, fine-tune, and deploy LLMs efficiently. Paul and Maxime have done an excellent job bridging the gap between theory and production engineering. You’ll learn about prompt optimization, retrieval-augmented generation (RAG), function calling, model evaluation, and more — all with actionable examples. I found this especially valuable for understanding the end-to-end lifecycle of LLM products and how to turn research models into production-ready systems. Here is the link to get the book — The LLM Engineering Handbook 2. AI Engineering — Chip Huyen Chip Huyen’s AI Engineering explores how modern AI applications are designed and scaled in real-world settings. It’s a perfect follow-up if you’ve already learned the basics and want to understand infrastructure, data pipelines, and deployment challenges in the age of foundation models. What I like most about this book is how Chip emphasizes engineering discipline — reproducibility, monitoring, and CI/CD for ML systems — something most books skip entirely. Here is the link to get the book — AI Engineering 3. Designing Machine Learning Systems — Chip Huyen Another brilliant work by Chip Huyen, this book focuses more on machine learning system design — from data collection and labeling to model deployment and maintenance. It’s full of practical insights that align closely with what top tech companies expect in ML engineering roles. If you’re preparing for AI/ML interviews or aiming to design robust ML infrastructure, this is the most actionable book to start with. Here is the link to get the book — Designing Machine Learning Systems 4. Building LLMs for Production — Louis-François Bouchard & Louie Peters This book is a practical guide to bringing LLMs into production environments safely and efficiently. It covers serving strategies, fine-tuning methods, vector databases, and integrating LLMs with existing applications. What sets it apart is its focus on operational excellence — latency, cost optimization, and observability — topics rarely discussed in LLM literature but crucial for real-world success. Here is the link to get the book — Building LLMs for Production By the way, he also have a course based upon the book, if you want some active learning you can also combine his course with the book, here is the link Building LLMs for Production 5. Build a Large Language Model (from Scratch) — Sebastian Raschka, PhD Sebastian Raschka’s work stands out for its technical depth and clarity. This book walks you through every step of building a transformer model from scratch — tokenization, attention mechanisms, optimization, and fine-tuning. If you’re a developer who wants to move beyond using APIs and truly understand how these models work, this book is a must-read. It’s one of the best hands-on guides to the inner workings of LLMs. Here is the link to get the book — Build a Large Language Model (from Scratch) And, if you want, you can also combine this with this 10-Hours LLM Fundamentals (Video) for active learning. 10-Hours LLM Fundamentals (Video) How I Choose These Books? When selecting AI and LLM books, I look for three key things: practical relevance, technical depth, and author credibility. Books written by practitioners who’ve built production systems tend to offer the most actionable insights. I also favor those that include code samples, real-world deployment tips, and design considerations. I avoid books that are overly academic or focused solely on theory — the AI world moves too fast for that. The five titles above strike the right balance between understanding concepts and applying them effectively. They’ll remain valuable even as the technology continues to evolve. Other Noteworthy Reads (Also Worth Checking Out) While these didn’t make the top five, they’re still excellent resources depending on your focus: * Hands-On Large Language Models: Language Understanding and Generation — Great for those who want guided implementations. * Prompt Engineering for LLMs — Focused on mastering prompts and evaluation. * Building Agentic AI Systems — A deep dive into agentic reasoning and AI autonomy. * Prompt Engineering for Generative AI — Good for creative use cases and applied prompt design. * The AI Engineering Bible — A broad overview for engineers building scalable AI systems. * LLMs in Production — Covers best practices for productizing AI models. LLMs in Production: From language models to successful products Why Learn AI and LLM Engineering in 2026? LLMs are reshaping every part of software engineering — from search to coding assistants, chatbots, and reasoning agents. Understanding how to build, fine-tune, and scale these models gives you a massive competitive advantage. The knowledge from these books goes beyond just model training — you’ll learn about vector databases, evaluation strategies, prompt design, and system orchestration, which are critical in today’s AI-driven applications. If you want to future-proof your skills and stay relevant in 2025 and beyond, these books will help you build a strong foundation — from the mechanics of LLMs to the engineering mindset required to ship them at scale. Though, if you prefer courses over books then you can also start with the Generative AI with Large Language Models on Coursera (offered by DeepLearning.AI & AWS), its a great course to build your foundational knowledge on AI and LL. Generative AI with Large Language Models That’s all in this list of my favorite books to learn AI and LLM engineering in 2026. Each of these recommendations is based on hands-on reading and practical application. I’ve used many of these insights in my own AI projects — and the difference they make is undeniable. You can find all these books through their official links above. I’ve included my affiliate links for convenience; they help support my writing at no extra cost to you. Start with one, but aim to read them all. The AI revolution isn’t waiting — and the best time to level up is now. Other AI, LLM, and Machine Learning resources you may like * Top 5 Courses to Prepare for AIF-C01 Exam in 2025 * 16 System Design Resources for Software Engineers * How to Prepare for AWS Solution Architect Exam in 2025 * Top 5 Udemy courses to build AI Agents in 2025 * 7 Best Courses to learn AWS S3 and DynamoDB in 2025 * 10 Best Udemy Courses to learn Artificial Intelligence in 2025 * 5 Best Udemy courses to learn Midjourney in 2025 * 6 Udemy Courses to learn AWS Bedrock in 2025 * Top 5 Udemy Courses for AWS Cloud Practitioner Exam in 2025 * 5 Best Courses to learn AWS SageMaker in 2025 * 8 Udemy courses to learn Prompt Engineering and ChatGPT * 5 Best Udemy Courses to learn Building AI Agents in 2025 * Top 5 Udemy Courses to learn Large Language Model in 2025 Thanks a lot for reading this article so far, if you like these AI and LLM Engineering books then please share with your friends and colleagues. If you have any feedback or questions then please drop a note. P. S. — You can also combine this book with a course like LLM Engineering: Master AI, Large Language Models & Agents to get some hands-on experience on building RAG based chatbot and learning LLM by watching. Top 5 Udemy Courses to Learn Large Language Models (LLMs) in 2025 --- I’ve Read 20+ Books on AI and LLM — Here Are My Top 5 Recommendations for 2026 was originally published in Javarevisited on Medium, where people are continuing the conversation by highlighting and responding to this story.

Hello guys, if you are interested in learning SQL with MySQL database and looking for some awesome resources e.g. books, tutorials, and online courses then you have come to the right place. In past, I have shared some useful books and tutorials and in this article, I am going to talk about some of the best MySQL online courses from Udemy, Coursera, and Pluralsight which you can join to learn SQL and MySQL from the comfort of your office or home. In the last couple of years, you might have heard the statement that everybody should learn to code, which is great. Coding is now like reading, writing, and speaking skills and in today's Information technology-centric world it is a must-have and there is no better way to start coding than learning SQL, the most popular programming language. --- Java, Unix, Tibco RV and FIX Protocol Tutorial

My favorite Udemy courses to Learn Crew AI in 2026 Continue reading on Javarevisited »

Codemia.io 65% OFF Lifetime Plan — Is It Worth It for #FAANG Interview Prep? Why I took Codemia.io lifetime plan for System Design interview If you’ve ever prepared for a FAANG interview — or any top-tier tech company interview — you already know one truth: cracking the system design round is brutally hard. Many candidates spend months solving LeetCode problems, mastering algorithms, and brushing up on data structures, only to get completely stumped when faced with an open-ended system design question like: * “Design a scalable messaging platform like WhatsApp.” * “How would you design a URL shortening service like Bit.ly?” * “Build a distributed file storage system.” Unlike coding challenges with clear inputs and outputs, system design interviews test your ability to architect real-world systems, make trade-offs, and communicate your ideas effectively — all under time pressure. Here’s the kicker: just knowing concepts isn’t enough. You might understand what caching, sharding, or load balancing is, but can you confidently apply those ideas to design an efficient, scalable system on the fly? That’s where most candidates struggle. This is exactly the gap that Codemia.io aims to fill. And right now, they’re offering an unbeatable 65% OFF lifetime plan — which makes this the perfect time to level up your skills. In this post, I’ll break down: * What Codemia.io is and how it works * Why system design interviews are tough (and how Codemia helps) * A detailed look at Codemia’s features and pricing * How it complements other popular resources like ByteByteGo * My honest take on whether the lifetime plan is worth it Let’s dive in. Why System Design Interviews Are So Difficult System design interviews are unlike any other part of the tech hiring process. Coding challenges can be mastered with repetition, but design questions require a deep understanding of distributed systems, trade-offs, scalability, and communication skills. Here’s why they’re uniquely tough: * Open-ended problems: There’s no single “correct” answer. Interviewers want to see your thought process, ability to handle ambiguity, and skill in balancing trade-offs. * Real-world scale: You’re asked to design systems like Netflix, Twitter, or Uber, where billions of requests happen every day. This requires practical knowledge of caching, databases, replication, and more. * Communication under pressure: You need to clearly explain your choices, justify trade-offs (e.g., SQL vs NoSQL, monolith vs microservices), and adapt as interviewers push back. You can read books, watch videos, and learn every concept in theory — but until you practice applying these ideas, you won’t feel confident in an actual interview. Enter Codemia.io — A Practice-First System Design Platform Codemia.io is a hands-on, interactive platform designed specifically for System Design Interview preparation. Unlike static courses or books, Codemia focuses on active learning — solving real system design problems and getting feedback to improve. Here’s what makes it stand out: * 120+ System Design Problems: Covering everything from social networks and messaging apps to e-commerce platforms and distributed databases. * 60+ Editorial Solutions: Expert-written explanations so you can compare your answers with best practices. * Object-Oriented Design Problem Set: Strengthen your fundamental design skills beyond large-scale systems. * Unlimited Iterative & Interactive AI Learning: Submit solutions, receive AI-powered feedback, and improve in real time. * Full Feedback History: Track your progress and revisit past solutions to identify growth areas. * Solution Sharing for Peer Feedback: Learn collaboratively by comparing approaches with other engineers. * Easy-to-Use UI on Desktop & Mobile: Practice anywhere, anytime. Instead of just reading about system design, you’ll be actively designing systems, making mistakes, and refining your solutions until you can confidently tackle any question. Here is the link to learn more: explore codemia.io The Current Offer — 65% OFF Lifetime Plan Codemia is currently running a limited-time promotion that gives you 65% off their lifetime plan. At just $159.20 one-time, the lifetime plan costs less than a single coding bootcamp course but gives you permanent access to a constantly updated system design library. Considering that system design skills remain relevant for your entire career, this is a bargain. 👉 Grab Codemia Lifetime Plan — 65% OFF Here Why Codemia.io Complements Other Resources Many engineers preparing for system design interviews start with popular platforms like: * ByteByteGo (for theory and visual explanations) * Grokking the System Design Interview * Books like Designing Data-Intensive Applications by Martin Kleppmann These are all excellent resources for learning concepts — but concepts alone won’t get you hired. You need to apply what you’ve learned to open-ended problems and refine your answers with feedback. This is where Codemia shines: * ByteByteGo is fantastic for learning theory. * Codemia is perfect for practicing application. * Using both gives you the best of both worlds. If you’re already using ByteByteGo or planning to get their lifetime plan, Codemia is the ideal companion to make sure you can apply those concepts in an interview setting. How Codemia Helps with FAANG Interview Prep FAANG companies (Facebook/Meta, Amazon, Apple, Netflix, Google) are known for their rigorous hiring process. System design rounds are typically 45–60 minutes and focus on evaluating: * Your ability to analyze ambiguous requirements * How well you can design scalable systems under real-world constraints * Your communication and trade-off analysis skills Codemia’s interactive, iterative approach helps you: * Develop a repeatable framework for tackling any design problem. * Practice structuring your answers to handle follow-up questions. * Build confidence by solving FAANG-level problems before the real interview. This isn’t just about passing interviews — it’s about becoming a better engineer who can architect scalable, reliable systems. Lifetime Plan vs. Annual Plan — Which One Should You Pick? Let’s be honest: the annual plan is attractive if you’re on a budget or have interviews scheduled soon. But if you’re serious about a long-term career in software engineering, the lifetime plan is the smart investment. Here’s why: * Cost Efficiency: The lifetime plan is roughly the cost of just 3 years of the annual plan. If you plan to revisit system design (and you will), it pays for itself. * No Renewal Hassles: Interviews don’t stop after one job. Promotions, career switches, or new roles will require system design prep again and again. * Lifetime Updates: Codemia continuously adds new problems, editorial solutions, and features — all included in the lifetime plan at no extra cost. If you ask me, I highly recommend you to take the lifetime plan and set for the life. The discount is also very good to lock in before the price is moved. Here is the link to learn more — Codemia.io annual and lifetime plan Tips to Maximize Codemia.io To get the most out of Codemia: * Start with Fundamentals: Tackle basic problems to build confidence before moving to FAANG-level challenges. * Use the AI Feedback: Don’t just glance at solutions — read feedback carefully and revise. * Simulate Real Interviews: Set a 45-minute timer and explain your design out loud as if an interviewer is listening. * #Review Past Attempts: Revisit old solutions to track growth and identify recurring mistakes. How Codemia Fits into a Complete Interview Strategy For best results, combine Codemia with: * LeetCode / HackerRank for coding rounds * ByteByteGo or Designing Data-Intensive Applications for conceptual understanding * Behavioral Prep (e.g., STAR method) for HR interviews This three-pronged strategy — coding + concepts + practice — will give you a huge edge over other candidates. Final Thoughts — Is Codemia.io Worth It? If you’re serious about cracking FAANG system design interviews, Codemia.io is absolutely worth it — especially at the current 65% off lifetime deal. System design isn’t just about memorizing patterns; it’s about thinking critically, making trade-offs, and communicating effectively. Codemia gives you the hands-on practice you need to master those skills, while the lifetime plan ensures you’ll always have access to new problems as your career evolves. For just $159.20 one-time, you’re not just buying a prep tool — you’re investing in a resource that will support you every time you face a new system design challenge, whether it’s for a new job, a promotion, or a personal project. 👉 Grab Codemia Lifetime Plan — Save $299.80 Today This is one of those rare investments that pays off every time you interview — and every time you build systems in the real world. Other System Design and Coding Interview and Resources you may like * 16 Best Resources for System Design Interview Prep * How Codemia.io helped me to learn System Design better? * 10 Reasons to join Codemia.io for System Design Interview? * Is DesignGuru’s System Design Course worth it * I found Codemia.io — LeetCode for System Design? * Why ByteByteGo is the best website for Coding interview in 2025? * Why AlgoMonster is best platform for DSA Prepration in 2025 * Is Exponent’s System Design Course worth it? * Is OOP Design Interview — An Insider Guide worth it? * ByteBytego vs Exponent? which one is better? * 10 Best Places to Learn System Design in 2025 * 10 Reasons to Learn System Design in 2025 * Is Exponent Good Place for Coding Interview Prep? * 6 Best System Design and API Design Interactive Courses * Top 5 System Design YouTube Channels for Engineers * How to prepare for DSA for coding interviews? * 3 Places to Practice System Design Mock interviews * Is Designing Data-intensive application book worth reading? All the best for your System design and OOP Design Interviews, if you have any doubts or questions, feel free to ask in the comments.P. S. — If you just want to do one thing at this time then I suggest you to join Codemia.io and start practicing system design problems. The best way to learn is by doing and learn when you get stuck. Master System Design Interviews Through Active Practice --- Codemia.io 65% OFF Lifetime Plan — Is It Worth It for FAANG Interview Prep? was originally published in Javarevisited on Medium, where people are continuing the conversation by highlighting and responding to this story.

Hello guys, if you want to become a full-stack Java developer and are looking for free online Java Full-stack development courses to kickstart your career, you have come to the right place. Earlier, I have shared the best Java full-stack development courses, and today, I will share 10 of the free online courses you can join to become a full-stack Java developer. The long journey of becoming a full-stack Java developer is not easy. You need to know all the details, from the front end to the backend. Not only these, but you also need to know how things function in databases and connectivity. --- Java Interview questions and tutorials

Hello guys, I have always said that there is no better way to learn anything then actually doing it and its 100% true for Spring Boot, one of the popular Framework for Java application Development. In my 20 years of experience, I have found that the best way to learn Java and Spring Boot is building projects. When you build project, common task surface them like creating a List or sorting a List and then you research and learn. Those learning stuck and make you better developer. Building project also have many advantage like it allows you to use a lot of technologies like Git, IntelliJIDEA, Hibernate, APIs etc together to build something which you can showcase to your potential employer.  --- Java Interview questions and tutorials

A comprehensive guide to understanding maps, their challenges, and when to choose HashMap or ConcurrentHashMap.

In the world of web development, the Spring Framework is widely known for its versatility and ease of use. It provides several annotations that simplify the process of handling HTTP requests and mapping them to specific methods in Spring controllers. Among these annotations, @GetMapping, @PostMapping, @PutMapping, @DeleteMapping, and @PatchMapping are some of the most commonly used ones. In this article, we will explore each of these annotations in detail, highlighting their purposes, differences, and providing examples to better understand their usage. --- Java Interview questions and tutorials

Hello guys, if you want to learn Java Programming from scratch and looking for the best Java course to join then you have come to the right place. Earlier, I have shared the best Java Programming courses, and today, I am going to review Java Programming Masterclass for Software Developers by Tim Buchalka, one of the highest-rated Java courses from Udemy. This course was also known as The Complete Java Masterclass before and now its known as Java 17 Masterclass: Start Coding in 2025. I have mentioned this course multiple times throughout different articles because it's currently the best course to learn Java. It's both comprehensive and up-to-date and most importantly it's very cost-effective. You can buy this 80-hour comprehensive course for just $10 which is just amazing.  --- Java, Unix, Tibco RV and FIX Protocol Tutorial

My favorite Frontend Masters courses to learn #Golang in 2026 Go (also known as Golang) has become one of the most sought-after #programming languages in 2026. Created by Google, Go powers some of the world’s most critical infrastructure — Docker, Kubernetes, Terraform, and countless microservices at companies like Uber, Netflix, and Dropbox. If you’re a developer looking to learn Go, you’re making a smart career move. Go developers are in high demand, with salaries often 20–30% higher than average backend developer positions. But here’s the challenge: finding high-quality, practical Go courses that teach real-world development, not just syntax. That’s where Frontend Masters comes in. Yes, you read that right — Frontend Masters, despite the name, has some of the best backend development courses available, including exceptional Go programming courses. I’ve spent the last few months going through their Go curriculum, and I’m excited to share the top courses that will take you from Go beginner to building production-ready web applications. These aren’t just theory courses — you’ll build real applications, understand concurrency patterns, and learn the Go idioms that separate professional Go developers from tutorial followers. Why Learn Go in 2026? Before diving into the courses, let’s address why Go is worth your time: 1. Performance & Efficiency * Compiled language with near-C performance * Low memory footprint compared to Java or Node.js * Fast compilation times (unlike C++) * Perfect for microservices and cloud-native applications 2. Simplicity & Productivity * Clean, minimalist syntax (25 keywords vs. Java’s 50+) * Built-in concurrency with goroutines and channels * Comprehensive standard library * Single binary deployment (no dependencies!) * Fast learning curve (productive in weeks, not months) 3. Strong Job Market * High demand for Go developers in cloud infrastructure * Companies like Google, Uber, Dropbox, and Twitch use Go extensively * Average Go developer salary: $120,000-$160,000 in US * Growing adoption in fintech, DevOps, and microservices 4. Modern Tooling * Excellent built-in tools (gofmt, go test, go mod) * Strong ecosystem for web development, CLI tools, and system programming * Great IDE support (VS Code, GoLand) * Active, helpful community Now, let’s explore the courses that will make you a Go expert. 1. Basics of Go by Maximiliano Firtman #Course Link Instructor: Maximiliano Firtman If you’re completely new to Go, this is THE place to start. Maximiliano Firtman is an exceptional teacher who makes Go’s concepts accessible without oversimplifying. What You’ll Learn: * Go fundamentals — Variables, types, and basic syntax * Functions and methods — Understanding Go’s approach to functions * Structs and interfaces — Go’s unique take on object-oriented programming * Error handling — Go’s explicit error handling patterns * Pointers — Understanding memory management in Go * Packages and modules — Organizing Go code properly * Basic concurrency — Introduction to goroutines and channels * Standard library — Essential packages every Go developer uses * Practical exercises — Hands-on coding throughout Why I Love This Course: Max doesn’t waste time. This course is laser-focused on getting you productive with Go as quickly as possible. He explains why Go does things differently from other languages, which helps if you’re coming from JavaScript, Python, or Java. What impressed me most was how Max introduces Go’s unique features — like defer statements, multiple return values, and interfaces — in a way that makes immediate sense. He doesn’t just show syntax; he explains the philosophy behind Go’s design decisions. The pacing is perfect for beginners. You’re not overwhelmed with advanced concepts too early, but you’re also not bored with trivial examples. By the end of this course, you’ll understand Go’s fundamentals and be ready to build simple applications. Perfect For: * Complete Go beginners with programming experience in other languages * JavaScript/Python developers learning backend development * Anyone who wants a solid foundation before building web applications * Developers preparing for the more advanced Go courses Key Takeaway: This course gives you a strong mental model of how Go works. You’ll understand why Go developers love the language’s simplicity and why companies choose Go for performance-critical systems. Pro Tip: Take this course first, then move to the Complete Go course for full-stack development. The progression is perfect. 2. Complete Go for Professional Developers by Melkey Course Link Instructor: Melkey This is the crown jewel of Go courses on Frontend Masters. If you’re serious about building production-ready web applications with Go, this is your masterclass. What You’ll Learn: * Advanced Go patterns — Professional-level Go idioms * Building web applications — HTTP servers, routing, middleware * Database integration — Working with SQL databases in Go * Authentication & authorization — Building secure applications * Template rendering — Server-side rendering with Go templates * File handling — Uploads, downloads, and file processing * Testing — Writing comprehensive tests in Go * Deployment — Getting your Go apps to production * Real-world project — Building a complete web application from scratch Why This Course Is a Game-Changer: Melkey takes you from Go basics to building a complete, production-ready web application. This isn’t a toy project — you’ll build something you could actually deploy and use. The course covers the entire stack: HTTP routing, database queries, user authentication, template rendering, and deployment. You’ll learn Go’s standard library thoroughly, which is crucial because Go’s philosophy is to use the standard library wherever possible. What sets this course apart is the focus on professional patterns. Melkey shows you how to structure your Go applications for maintainability, how to handle errors gracefully, and how to write tests that catch bugs before production. The hands-on approach is fantastic. You’re constantly coding, not just watching. By the end, you’ll have a portfolio piece and the confidence to build Go applications professionally. Perfect For: * Intermediate Go developers ready for production development * Backend developers wanting to specialize in Go * Full-stack developers adding Go to their toolkit * Anyone building microservices or APIs * Developers preparing for Go engineering roles Key Takeaway: This is the course that transforms you from “I know Go syntax” to “I can build professional Go applications.” After this, you’re job-ready. Must-Know: This course assumes you understand Go basics. Take the “Basics of Go” course first if you’re completely new to the language. 3. Go & Vanilla JS: Fullstack Without Frameworks by Maximiliano Firtman Course Link Instructor: Maximiliano Firtman This unique course shows you how to build full-stack applications using Go for the backend and vanilla JavaScript for the frontend — no React, no Vue, no framework bloat. What You’ll Learn: * Go HTTP servers — Building RESTful APIs with Go * Routing and middleware — Handling requests professionally * Database integration — PostgreSQL with Go * API design — RESTful patterns and best practices * Vanilla JavaScript — Building dynamic frontends without frameworks * WebSockets — Real-time communication in Go * Authentication — Session management and JWT * CORS and security — Protecting your APIs * Full-stack architecture — Connecting frontend and backend * Deployment — Shipping your application to production Why This Course Stands Out: Max challenges the framework-heavy approach to web development. Instead of reaching for Next.js or Express, you’ll learn to build everything from scratch using Go’s standard library and vanilla JavaScript. This approach has massive benefits: * No dependency hell: Your app has minimal dependencies * Blazing fast: Go’s performance + no framework overhead * Deep understanding: You learn how things actually work * Long-term maintainability: Less code to break when dependencies update The course is incredibly practical. You build a complete full-stack application, handling everything from database queries to DOM manipulation. It’s challenging but rewarding. Perfect For: * Go developers wanting to add full-stack skills * Developers tired of JavaScript framework churn * Anyone building internal tools or MVPs quickly * Teams wanting lightweight, performant applications * Developers who value understanding over abstraction Key Takeaway: You don’t need frameworks to build great web applications. Go’s standard library + vanilla JavaScript is powerful, performant, and often simpler than framework-based solutions. This course will change how you think about web development. You’ll appreciate the simplicity of building without layers of abstraction. 4. Introduction to Backend Architectures (with Go Examples) Course Link While not exclusively a Go course, this course uses Go extensively to teach backend architecture patterns, making it essential for Go developers building scalable systems. What You’ll Learn: * Backend architecture patterns — Monoliths, microservices, serverless * API design principles — REST, GraphQL, and when to use each * Database architectures — SQL, NoSQL, and choosing the right database * Caching strategies — Redis and in-memory caching with Go * Message queues — Asynchronous processing patterns * Service communication — gRPC, HTTP, and message brokers * Scalability patterns — Horizontal scaling, load balancing * Monitoring and observability — Logging and metrics in Go * Security best practices — Authentication, authorization, and data protection Why This Course Is Essential: Go is often chosen for building scalable backend systems. This course teaches you the architectural knowledge needed to build those systems properly. You’ll learn when to use microservices vs. monoliths, how to design APIs that scale, and how to implement caching and message queues. All examples use Go, so you’re learning architecture while reinforcing your Go skills. What I appreciated most was the focus on trade-offs. The instructor doesn’t advocate for one pattern over another; instead, they explain when each approach makes sense and what problems each solves. Perfect For: * Go developers moving to senior or architect roles * Backend engineers designing scalable systems * Anyone building microservices with Go * Developers preparing for system design interviews * Teams transitioning from monoliths to distributed systems Key Takeaway: Go is a great language for backend development, but knowing the language isn’t enough. You need to understand backend architecture to build systems that scale and survive in production. This course gives you that architectural knowledge while strengthening your Go skills. 5. Complete Intro to Linux and the Command-Line by Brian Holt Course Link Instructor: Brian Holt “Wait,” you might think, “this isn’t a Go course!” You’re right, but hear me out. Go developers almost always work in Linux environments, and understanding Linux deeply makes you a better Go developer. What You’ll Learn: * Linux fundamentals — Understanding the OS Go runs on * Command-line mastery — Becoming productive in the terminal * Shell scripting — Automating tasks with bash * Process management — Understanding how Go programs run * File systems — How Linux handles files and permissions * Networking basics — Essential for Go backend development * Package management — Installing tools and dependencies * SSH and remote servers — Deploying Go applications * Environment variables — Configuration management for Go apps * System monitoring — Understanding CPU, memory, and disk usage Why Go Developers Need This: Go is designed for building server applications that run on Linux. Understanding Linux makes you a more effective Go developer because: * Deployment confidence: You’ll know how to deploy and manage Go applications * Debugging skills: Understanding system calls and processes helps debug Go apps * Performance tuning: You’ll understand how Go interacts with the OS * DevOps integration: Go developers often wear DevOps hats * Production readiness: You’ll know how to configure environments properly Brian Holt is one of Frontend Masters’ best instructors. He makes Linux approachable and even fun. The course is hands-on, with lots of exercises that build muscle memory. Perfect For: * Go developers who primarily work on Windows/Mac * Backend engineers strengthening their Linux skills * Anyone deploying Go applications to servers * Developers preparing for DevOps or SRE roles * Teams adopting Go for cloud-native development Key Takeaway: Go and Linux are best friends. Mastering Linux makes you a more confident, capable Go developer. When something goes wrong in production (and it will), you’ll know how to investigate and fix it. How to Choose Your Go Learning Path With these excellent courses, how do you decide your learning journey? Here are my recommendations based on your goals: Complete Beginner Path (Fastest to Job-Ready): * Start: Basics of Go * Then: Complete Go for Professional Developers * Finally: Complete Intro to Linux Result: Production-ready Go developer with deployment skills Full-Stack Developer Path: * Start: Basics of Go * Then: Go & Vanilla JS: Fullstack Without Frameworks * Optional: Complete Go for Professional Developers Result: Full-stack Go developer who can build complete applications Backend Architecture Path (For Senior Roles): * Start: Basics of Go * Then: Complete Go for Professional Developers * Finally: Introduction to Backend Architectures Result: Senior-level Go developer ready for architecture discussions DevOps/Infrastructure Path: * Start: Complete Intro to Linux * Then: Basics of Go * Finally: Complete Go for Professional Developers Result: Go developer with strong infrastructure knowledge Complementary Courses to Supercharge Your Go Learning While learning Go, consider these additional Frontend Masters courses that complement your skills: Complete Intro to Databases Learn PostgreSQL, MongoDB, and Redis — databases commonly used with Go applications. API Design in Node.js, v4 While it uses Node.js, the API design principles apply perfectly to Go. Complete Intro to Containers, v2 Learn Docker — essential for deploying Go applications. Everything You’ll Need to Know About Git Master Git workflows for professional Go development. Getting the Most Out of Frontend Masters for Go Here’s how to maximize your learning on Frontend Masters: 1. Get the Annual Subscription At $390/year (or $39/month), a Frontend Masters membership gives you access to 200+ courses. For Go developers, this is invaluable because you’ll want to explore databases, DevOps, system design, and more. The annual plan is $32.50/month — less than a lunch per week. For the depth and quality of Go instruction, it’s an absolute steal. 2. Follow the Learning Paths Frontend Masters has curated learning paths that guide you through related courses in a logical order. While there isn’t a specific “Go” path yet, the “Professional” path includes many backend-relevant courses. 3. Code Along, Don’t Just Watch Every course has exercises and projects. Type the code yourself. Don’t copy-paste. The muscle memory and debugging experience you gain is where the real learning happens. 4. Build Your Own Projects After each course, build something from scratch: * After “Basics of Go”: Build a CLI tool * After “Complete Go”: Build an API for a personal project * After “Fullstack”: Build a complete web application 5. Explore Free Content First Frontend Masters offers some courses for free. Try these to experience the teaching quality before committing to a subscription. 6. Check Out Popular Courses Browse courses sorted by popularity to discover other highly-rated content that complements your Go learning. Meet the Instructors Maximiliano Firtman Max is a mobile and web development expert who brings clarity to complex topics. His teaching style is clear, concise, and practical. He has a knack for explaining why things work, not just how. Check out Max’s other courses Melkey Melkey specializes in backend development and brings real-world experience to the classroom. His course on building web applications with Go is comprehensive and production-focused. Brian Holt One of Frontend Masters’ most popular instructors, Brian Holt has a gift for making technical topics approachable and even fun. His Linux course is essential for any Go developer. Why Frontend Masters for Go Development? You might wonder: “Why Frontend Masters for backend/Go courses?” Here’s why: 1. Instructor Quality Frontend Masters instructors are practicing developers, not just teachers. They bring real-world experience from production systems. 2. Depth Over Breadth Courses go deep. A 4-hour Go course on Frontend Masters covers more than a 20-hour Udemy course because every minute is dense with valuable content. 3. Modern, Updated Content Courses use current Go versions and modern best practices. You’re learning Go as it’s written today, not outdated patterns. 4. No Fluff Zero wasted time. No long intros, no “smash that subscribe button,” just pure, valuable instruction from expert practitioners. 5. Professional Production High-quality video and audio, well-structured courses, excellent code examples. The platform is a joy to use. 6. Beyond Go Your subscription includes courses on databases, Docker, Kubernetes, system design, and more — all essential for Go developers. Common Go Learning Challenges These Courses Solve “I don’t understand goroutines and channels” Solved in: Basics of Go, Complete Go for Professional Developers These courses dedicate significant time to Go’s concurrency model, with practical examples that make goroutines and channels click. “I can write Go syntax but can’t build real applications” Solved in: Complete Go for Professional Developers, Fullstack Without Frameworks Both courses focus on building complete, production-ready applications from scratch. “I don’t know how to structure Go projects” Solved in: Complete Go for Professional Developers Melkey shows professional Go project structure, package organization, and separation of concerns. “I struggle with Go’s error handling” Solved in: All Go courses Each course emphasizes Go’s explicit error handling, showing patterns for graceful error handling in production code. “I don’t know how to deploy Go applications” Solved in: Complete Go, Complete Intro to Linux Learn both the application side and the infrastructure side of deploying Go apps. “I can’t decide between microservices and monoliths” Solved in: Introduction to Backend Architectures Understand the trade-offs and make informed architectural decisions. Real-World Impact: Before and After Go Here’s what changed after I completed these Go courses: Before: * Struggled with concurrency patterns * Copied code without understanding why * Avoided deploying applications * Couldn’t explain Go’s advantages over other languages * Took days to build simple APIs After: * Confidently use goroutines and channels * Write idiomatic Go code that passes code review * Deploy Go applications to production independently * Articulate Go’s strengths in technical discussions * Build production APIs in hours, not days Career Impact: * Landed a backend engineer role at 40% salary increase * Became the Go expert on my team * Contributed to open-source Go projects * Built internal tools that saved team 10+ hours/week * Interviewed successfully at companies using Go Is Frontend Masters Worth It for Go Developers? Let’s do the math: Frontend Masters Annual Subscription: $390 Go courses available: 5+ (and growing) Total course hours: 20+ hours of Go content Plus: 200+ courses on related topics (databases, DevOps, system design) Alternatives: * Go bootcamp: $5,000-$15,000 * Private tutoring: $75-$150/hour * College course: $1,500-$5,000 * Frontend Masters: $390 for everything Even taking just the Go courses, you’re getting expert instruction for less than $100 per course. Plus, you get access to complementary courses on databases, Linux, Docker, and system design. The value is undeniable. Getting Started with Go on Frontend Masters Today Ready to become a Go developer? Here’s your action plan: Step 1: Choose Your Path Pick one of the learning paths I outlined earlier based on your goals (beginner, full-stack, architecture, or DevOps). Step 2: Subscribe to Frontend Masters Get your Frontend Masters membership and get immediate access to all Go courses and 200+ other courses. Step 3: Set a Schedule Block out 30–60 minutes daily for learning. Consistency beats intensity — daily practice compounds quickly. Step 4: Start with Basics Begin with Basics of Go regardless of your ultimate goal. Solid fundamentals make everything else easier. Step 5: Build Projects After each course, build something from scratch. GitHub repos are your portfolio — fill them with Go projects. Step 6: Join the Community Connect with other Go learners in the Frontend Masters community and on the Go subreddit, Discord servers, and forums. Frequently Asked Questions Q: Do I need to know any programming language before learning Go? A: Yes. These courses assume you understand programming basics (variables, loops, functions). If you’re brand new to programming, learn Python or JavaScript first, then return to Go. Q: How long does it take to become job-ready with Go? A: If you follow the Complete Beginner Path and code daily, you can be job-ready in 2–3 months. Focus on building projects — employers hire based on what you can build, not courses completed. Q: Is Go better than Node.js or Python for backend development? A: “Better” depends on context. Go excels at performance, concurrency, and simple deployment. Node.js has a larger ecosystem. Python has better data science integration. Choose based on your project needs. Q: Can I watch courses on mobile? A: Yes! Frontend Masters has excellent mobile apps for iOS and Android, perfect for learning during commutes. Q: Will I get a certificate? A: Yes, you get a completion certificate for each course. While not accredited, they demonstrate your commitment to learning. Q: What if I get stuck on a course? A: Each course has a Q&A section where you can ask questions. The instructors and community are responsive and helpful. Final Thoughts: Why Go, Why Now, Why Frontend Masters? Go isn’t just another programming language — it’s a philosophy of software development that emphasizes simplicity, readability, and performance. Companies are betting their infrastructure on Go, and the demand for Go developers is only increasing. These Frontend Masters courses represent the best Go education available online. The instructors are world-class practitioners, the content is comprehensive and practical, and the projects are portfolio-worthy. Whether you’re a frontend developer expanding to backend, a Python developer seeking better performance, or a Java developer embracing simplicity, Go is the right choice. And Frontend Masters is the right place to learn it. The question isn’t “Should I learn Go?” It’s “When will I start?” Start your Go journey today: * Join Frontend Masters * Start with Basics of Go * Explore all courses * Check learning paths Your future as a Go developer starts now. The infrastructure of tomorrow is being built in Go today — be part of it. Happy coding! 🚀 What made you interested in learning Go? Are you building microservices, CLI tools, or something else? Let me know in the comments!

Hello folks, If you are learning Python Programming language for Web Development, then you may have heard about the Django framework. Django is one of the popular web development frameworks to create modern web applications using the Python programming language. Django is also the most popular and most mature Python web development framework around. It makes it easier to build better Web apps more quickly and with less code. Building websites with Django is not just smart and efficient, but fun too! Learning Django can also boost your CV as it's a very in-demand skill. --- Java, Unix, Tibco RV and FIX Protocol Tutorial

#Review — Is Certified #Blockchain Product Manager (CBPM) Certification Worth it? Doe certified Blockchain Product Manager (CBPM) certification on 101 Blockchain Academy really worth it? Hello guys, 101 Blockchain recently launched a new Certified Blockchain Product Manager (CBPM) and I got a chance to look at this highly sought after program. As blockchain continues to transform industries — from finance and supply chain to gaming and digital identity the need for professionals who can bridge technology and business strategy has never been greater. One emerging role in this space is the Blockchain Product Manager, someone who can translate Web3 ideas into scalable, compliant, and user-friendly products. If you’re considering entering this space, the Certified Blockchain Product Manager (CBPM)™ certification by 101 Blockchains is one of the most respected and practical programs available. In this review, we’ll break down what it offers, who it’s for, and whether it’s worth your investment. What Is the Certified Blockchain Product Manager (CBPM)™? The CBPM™ certification is designed to help you master blockchain and Web3 product management from the ground up — covering fundamentals, tokenomics, governance, compliance, and community building. It’s ideal for: * Product managers and project leads transitioning into blockchain and Web3. * Entrepreneurs and startup founders developing blockchain-based products. * Business analysts and consultants working on enterprise blockchain use cases. * Developers and engineers looking to gain business and product management skills. You’ll learn how to: * Understand blockchain fundamentals and Web3 architecture. * Design sustainable tokenomics and incentive models. * Build community and governance structures for decentralized ecosystems. * Conduct market research and develop real-world use cases. * Plan product launches and scalability strategies. Overall this is a very well structured program to not just learn about Blockchain fundamentals and Web3 architecture but also build community and governance structures for decentralized ecosystems. Here is the link to join this program — Certified Blockchain Product Manager (CBPM)™ Why Consider CBPM™ from 101 Blockchains? One of the biggest advantages of the CBPM™ is that it’s accredited by the CPD Certification Service, ensuring it meets international professional education standards. But more importantly, it’s practical — the lessons aren’t just theory. They’re structured to help you launch and manage blockchain products in real-world contexts, with examples, case studies, and exercises. The #course not only helps you understand blockchain at a technical level but also gives you the frameworks to think like a strategic product leader in a decentralized environment. What You’ll Learn Inside the Program? Here’s what you’ll cover: * Blockchain and Web3 fundamentals * Blockchain product management basics * Tokenomics, governance, and incentives * Market research and user-centric design * Community and ecosystem building * Product launch and scalability planning * Real-world blockchain product use cases By the end, you’ll have the toolkit to move from concept to launch with confidence — whether it’s a DeFi platform, NFT marketplace, or enterprise blockchain solution. 101 Blockchains Membership — A Better Deal for Learners When it comes to joining this certification, you have two options: You can enroll in the CBPM™ individually, or you can get a 101 Blockchains Membership, which gives you access to this and several other top-rated certifications for just $25 per month (on the yearly plan). It’s also a great place to learn emerging technologies like Artificial Intelligence, Web3, Metaverse, Blockchain and others. 👉 Check 101 Blockchains Pricing Plans This membership includes in-demand certifications like: * Certified Enterprise Blockchain Professional (CEBP) * Certified Fintech Expert (CFTE) * Certified Blockchain Security Expert (CBSE) * Certified Web 3.0 Professional (CW3P) * Certified AI Professional (CAIP) * Certified Metaverse Professional (CMP) For professionals serious about upskilling in blockchain, AI, and Web3, this membership provides exceptional value — especially with the current 50% discount on the annual plan. My Verdict: Is the CBPM™ Certification Worth It? Yes — if you’re aiming to move into blockchain or Web3 product management, the CBPM™ from 101 Blockchains is absolutely worth it. Here’s why: * It’s accredited and recognized across industries. * You gain hands-on, strategic knowledge, not just theory. * You can access it affordably through the membership plan ($25/month on annual billing). * It’s part of a larger ecosystem of Web3, AI, and Fintech certifications. So whether you’re an existing product manager looking to transition into Web3, or a developer aiming to move up the product leadership ladder, this certification offers a clear, guided path to do just that. 👉 Join the Certified Blockchain Product Manager (CBPM)™ Program on 101 Blockchains Other Blockchain and Technology articles you may like * 10 Best Blockchain Courses for Developers * 10 Best Udemy Courses to learn Blockchain in depth * Is Solana Development course from 101 Blockchains worth it? Review * 7 Free Courses to learn blockchain in 2025 * 101 Blockchain Review 2025 — why its best place to learn Blockchain? * Top 10 Courses to learn Blockchain and AI in 2025 * Is Certified Enterprise Blockchain Professional Certification (CEBP) worth it * Top 5 101 Blockchain Courses and Certifications * Review — Is Certified Blockchain Security Expert (CBSE) Certification by 101 Blockchains worth it? * Is 101 Blockchain Certification really worth it? * Review — Is Certified Web3 Professional (CW3P) on 101 Blockchains worth it * Review — Is Hyperledger Fabric Development course on 101 Blockchains worth it? * Is 101 Blockchains Academy’s Premium Plan Really Worth It? (50% OFF) Thanks for reading this article so far. If you like this article then please share with your friends and colleagues if you find them useful. If you have any questions or feedback, then please drop a note. P. S. — If you are serious about learning Blockchain technologies and looking for the best Blockchain certification to start with then this Enterprise Blockchain Certification by 101 Blockchain is the best resource to start with. Many of my students and readers have taken this course and feedback has been awesome. Review — Is Certified Enterprise Blockchain Professional Certification (CEBP) worth it? --- Review — Is Certified Blockchain Product Manager (CBPM) Certification Worth it? was originally published in Javarevisited on Medium, where people are continuing the conversation by highlighting and responding to this story.

Hello guys, if you are doing software development then you may know that as engineering teams scale, code review becomes not just a quality gate, but also an opportunity for mentorship, knowledge sharing, and upholding long-term code health. But sloppy reviews, unclear feedback, or bottlenecks can erode morale and slow down delivery. Here are 10 best practices I’ve refined over years of reviewing code at scale — each backed by experience — and how modern AI tools like CodeRabbit.ai can turbocharge your review workflow when used responsibly. --- Java Interview questions and tutorials

Why I took Codemia.io lifetime plan for System Design interview Hello guys, If you are preparing for system design interviews, you might have already come across Codemia.io — one of the most comprehensive platforms for mastering system design, object-oriented design, and iterative problem-solving. Codemia.io is trusted by software engineers around the world because it combines interactive learning, AI-powered feedback, and community collaboration, making it easier to prepare for interviews efficiently. While there are many platforms where you can learn System Design concepts like ByteByteGo, Design Guru, Exponent, and Educative, there are not many platforms where you can practice System Design question live online in a Leetcode style. I have always combined ByteByteGo and Codemia.io primarily along with other resources to prepare for my System Design interviews in last few years. But when it comes to subscribing, the big question is: Should you go for the annual plan, or is the lifetime plan worth the investment? Having personally explored the platform, I want to share my thoughts on why Codemia.io is a must-have resource for anyone serious about their career growth and why I chose their lifetime plan for my preparation. Master System Design Interviews Through Active Practice Why Codemia.io is a Must-Have for Interview Prep Codemia.io isn’t just a collection of problems. It’s a complete interview preparation ecosystem. Here’s why I think it’s one of the best tools for software engineers: * Comprehensive System Design Practice Codemia.io offers 120+ system design problems along with 60+ editorial solutions. Each problem comes with detailed structural breakdowns, object-oriented design examples, and real-world considerations to help you think like an experienced engineer. * Interactive Learning with AI Feedback The platform provides iterative, interactive AI learning, where you can submit solutions, receive AI feedback, and improve over time. This replicates the real-world interview cycle where iterative improvement matters the most. * Community & Peer Feedback Beyond AI, you can share your solutions with peers for review and discussion. This collaborative approach is invaluable for understanding different design perspectives and coding strategies. * Easy-to-Use, Multi-Device UI Codemia.io works seamlessly on both desktop and mobile. Whether you’re studying at home, commuting, or in a coffee shop, the platform adapts to your workflow. And the best part? Codemia.io is offering a significant discount on both their annual and lifetime plans right now, making this the perfect time to invest in your career. I personally took the lifetime plan because its not very expensive due to the huge 65% discount they are offering now. Since the cost of lifetime plan is just a couple of times annual plan it make sense to get that because you will be using this platform for a long time whenever you look for chance. Annual vs. Lifetime Plan: Which One Should You Choose? When I was evaluating Codemia.io, I considered both the annual and lifetime plans. Here’s a quick breakdown: Annual Plan — Most Popular * Cost: $47.20/year (billed annually, ~$3.93/month) * Savings: $71.80 off the regular price * Access: 1 year of content and updates * Best for: Short-term prep or if you only want a one-year subscription Lifetime Plan — Best Value * Cost: $159.20 one-time payment * Savings: $299.80 off the regular price * Access: Unlimited lifetime access to all content and future updates * Best for: Long-term career investment; you’ll never have to worry about renewing * Includes: All system design problems, editorial solutions, object-oriented design sets, iterative AI learning, peer feedback, and full solution history As I said I chose the lifetime plan because in my opinion it provided best value and I will also be immune to any future price update which is inevitable because they will be keep adding more questions and features in this platform to make it even more useful. If you ask me, I highly recommend you to take the lifetime plan and set for the life. The discount is also very good to lock in before the price is moved. Here is the link to learn more — Codemia.io annual and lifetime plan Why I Picked the Lifetime Plan? As I said, I picked the lifetime plan because it provided best value and System Design is an evergreen topic which will always be needed whenever I will look for chance and new opportunities Here are the key reasons why I chose the codemia.io lifetime plan: * Long-Term Cost Efficiency While the upfront cost is higher, the lifetime plan pays for itself in just a few years. Codemia.io is a resource you’ll return to throughout your career, whether preparing for interviews or revisiting complex system designs. * Continuous Learning System design interviews evolve constantly. Lifetime access ensures you automatically get new case studies, problems, and lessons without paying extra. * Peace of Mind No recurring payments, no subscription renewal worries. Your learning stays uninterrupted. * Immune from future price increase I will also be immune to any future price update but get access to all the new content that will be added into platform like new System Design questions. Due to all these reasons and the value I got from Codemia.io’s interactive online practice platform for System Design interview, I chose to enroll into their lifetime plan and I recommend the same to others. Here is the link — Join Codemia.io for 65% discount now My Take: Go Lifetime if You’re Serious If you’re aiming to ace multiple coding and system design interviews over the years, the lifetime plan is the smarter choice. The combination of structured problems, interactive AI feedback, community review, and lifetime updates makes Codemia.io one of the most valuable resources for technical interview prep. 👉 Check out Codemia.io Lifetime Plan here By the way, whether you choose annual or lifetime plan, Codemia.io equips you with laser-focused practice, high-quality content, and iterative mastery, helping you level up your system design and coding skills efficiently. Other System Design and Coding Interview and Resources you may like * 16 Best Resources for System Design Interview Prep * How Codemia.io helped me to learn System Design better? * 10 Reasons to join Codemia.io for System Design Interview? * Is DesignGuru’s System Design Course worth it * I found Codemia.io — LeetCode for System Design? * Why ByteByteGo is the best website for Coding interview in 2025? * Why AlgoMonster is best platform for DSA Prepration in 2025 * Is Exponent’s System Design Course worth it? * Is OOP Design Interview — An Insider Guide worth it? * ByteBytego vs Exponent? which one is better? * 10 Best Places to Learn System Design in 2025 * 10 Reasons to Learn System Design in 2025 * Is Exponent Good Place for Coding Interview Prep? * 6 Best System Design and API Design Interactive Courses * Top 5 System Design YouTube Channels for Engineers * How to prepare for DSA for coding interviews? * 3 Places to Practice System Design Mock interviews * Is Designing Data-intensive application book worth reading? All the best for your System design and OOP Design Interviews, if you have any doubts or questions, feel free to ask in the comments.P. S. — If you just want to do one thing at this time then I suggest you to join Codemia.io and start practicing system design problems. The best way to learn is by doing and learn when you get stuck. Master System Design Interviews Through Active Practice --- Codemia.io Annual vs. Lifetime Plan: Which One is best for System Design Interview? was originally published in Javarevisited on Medium, where people are continuing the conversation by highlighting and responding to this story.

How HTTP/2 enables true parallelism over a single connection

Hello guys, like many programmers, I have also worked with a lot of source control systems like SVN, CVS, TFS, VSS, Mercury, and I had always wondered why so many source control systems? Why not just one. It's one of the necessary software tools for development, and everyone needs a version control and code repository, there should be a standard solution. It seems Git and Github have solved that problem now. Now, Git is everywhere from open source to closed source, from small startups to big Investment banks, but there were still legacy projects which were lying on SVN and CVS, but they are now also started moving towards it. --- Java, Unix, Tibco RV and FIX Protocol Tutorial