Claudia Ng
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ds-claudia.bsky.social
Claudia Ng
@ds-claudia.bsky.social
I'm a...
🤖 Data scientist with 6 years in tech
🌏 Polyglot and traveler who’s lived on 4 continents

I write about…
🤖 Data science and AI: aiweekender.substack.com
🌏 Languages and travel: polyglotclaudia.substack.com
To all the engineers who got paged during the AWS outage last night: I feel for you.

Being on-call is rough.
Being on-call for something you can’t fix is existentially rough.

You’re out here rebooting servers at 3 a.m., praying the cloud gods show mercy.

Take a long nap today.
October 21, 2025 at 1:55 AM
When I was learning Python, I kept forgetting everything.

I’d ace a tutorial… then freeze the next day staring at a blank screen.

What helped wasn’t more studying. It was more doing.

Here's what I would tell myself if I could go back in time 👇
October 13, 2025 at 10:14 PM
In the past 2 weeks, 85 people tried my Cantonese AI partner:

213 conversations

993 interactions

A couple users came back 6–7 days straight

Most dropped after day 1

Now I’m stuck: Do I keep fixing bugs + adding features? Or pause and set up Stripe to see if anyone pays?
September 29, 2025 at 5:30 PM
I got a “fan message” for my AI prototype!!

It wasn’t about the tech. It wasn’t about features.

It said:

“Thank YOU so much for making this. I love it. I will keep going.”

🥹
September 29, 2025 at 5:13 PM
Reposted by Claudia Ng
@ds-claudia.bsky.social explains why domain expertise often outweighs algorithmic complexity. In this Author Spotlight, she reflects on her path from corporate ML to freelance AI, mentoring newcomers, and the lessons learned along the way.
“My biggest lesson was realizing that domain expertise matters more than algorithmic complexity.“ | Towards Data Science
Claudia Ng reflects on real-world ML lessons, mentoring newcomers, and her journey from corporate ML to freelance AI.
towardsdatascience.com
September 3, 2025 at 4:23 PM
Woke up to see AI Weekender ranked #51 in Tech on Substack 🎉

I started on Jan 23 with one goal: publish every Thursday.
Some posts hit, others sank.
But showing up each week built momentum.

Biggest lesson? Consistency compounds.

aiweekender.substack.com
August 19, 2025 at 9:28 PM
Reposted by Claudia Ng
✨ In our latest Author Spotlight, @ds-claudia.bsky.social, who successfully shifted from a corporate role to freelance, provides hard-won advice on navigating career paths, mentoring newcomers, and building solutions you truly own.
“My biggest lesson was realizing that domain expertise matters more than algorithmic complexity.“ | Towards Data Science
Claudia Ng reflects on real-world ML lessons, mentoring newcomers, and her journey from corporate ML to freelance AI.
towardsdatascience.com
August 14, 2025 at 9:05 PM
Every project should either:

- Build skills
- Build assets
- Build your brand

If it’s doing none, stop.
August 8, 2025 at 5:32 PM
As a solo data scientist, I’ve found 3 types of leverage:
- Coaching gave me human leverage
- Consulting gave me applied leverage
- Content and AI tools? That’s scalable leverage

Read more here:
open.substack.com/pub/aiweeken...
3 Solopreneur Paths for Data Scientists
What I'm building after corporate DS and the paths I've tried
open.substack.com
August 8, 2025 at 5:30 PM
I didn’t build my first RAG tool because I thought it would go viral.

I built it because people kept DM’ing me asking how to break into data science or build with AI, all questions I’d already answered in my posts.

Try it: assistant.ds-claudia.com
August 5, 2025 at 10:59 PM
I was tired of AI tutorials that felt like science fair projects.

So I built a real RAG project: it turns your Substack posts into a searchable AI assistant.

This post walks through every step: from scraping to chunking to shipping.

shorturl.at/GicNL
RAG Tutorial with Code: Ship Your Own AI Assistant This Weekend
The exact blueprint for building a RAG chatbot that will save you dozens of hours
shorturl.at
July 24, 2025 at 4:27 PM
Building an AI product in 5 steps:

1. Have an idea
2. Prompt like a maniac
3. Watch it almost work
4. Panic, then debug
5. Ship it anyway

Does this sound familiar, or is your chaos different?
July 23, 2025 at 7:50 PM
Most of AI building isn’t about being smart.

It’s about being stubborn enough to fix what breaks…

And curious enough to try again.
July 23, 2025 at 7:48 PM
Some projects take a weekend.

Some take months.

Both are valid.

Both move you forward.
July 23, 2025 at 7:44 PM
I don’t want to build flashy AI.

I want to build stuff people actually use.

aiweekender.substack.com/p/the-strate...
From Data Scientist to AI Builder: What Actually Works
How I learned to stop chasing tools and start solving problems
aiweekender.substack.com
July 23, 2025 at 7:43 PM
The real flex isn’t how smart your AI project is.

It’s how clearly you can explain it to a non-technical friend.
July 23, 2025 at 7:42 PM
Don’t aim for perfect.

Aim for finished.

Build momentum!
July 23, 2025 at 7:41 PM
I don’t build AI projects to impress anyone.

I build them to prove to myself I can.

Why do you do what you do?
July 23, 2025 at 7:40 PM
Most people are waiting for the confidence to begin.
But confidence is what you earn after you start.
July 23, 2025 at 7:40 PM
Your weekend build might not be world-changing.

But it might change your world:

Your confidence,

Your direction,

Your job.
July 22, 2025 at 9:05 PM
I write AI technical tutorials not because I know everything,

but because writing is how I figure things out.
July 22, 2025 at 9:04 PM
Genuine question: Do you consider vibe coding with AI "cheating"?

I see it like using:

- Calculators instead of long division, or
- GPS instead of memorizing maps, or
- Driving a car instead of walking.

Same destination, better tools.

What's your perspective?
July 21, 2025 at 6:40 PM
Cantonese diaspora: tired of sounding like a 5-year-old when talking to your grandmother?

I'm building an AI conversation partner where you can practice without judgment.

Looking for beta testers (30-min sessions) to shape this product! DM me.
July 21, 2025 at 6:35 PM
Most people learn AI tools then hunt for problems to use them on.

I learned to spot problems first, then pick the simplest tool that works.

My problem-first strategy: aiweekender.substack.com/p/the-strate...
From Data Scientist to AI Builder: What Actually Works
How I learned to stop chasing tools and start solving problems
aiweekender.substack.com
July 21, 2025 at 6:11 PM
Differences between production AI systems vs. demos:

Demo: Works perfectly in controlled environment

Production: Handles edge cases, rate limits, and vendor outages

The gap is where experience matters.
July 21, 2025 at 6:10 PM