Start Here: Non-Brand Data
A structured way to build practical data skills without learning randomly.
Hi there, Cornellius here!👋
Non-Brand Data helps you build in-demand data and AI skills with structure, so reading turns into shipped work.
Do this in order (5 steps)
Start with the Focus Map (Free PDF)
Download it and pick one track: SQL, Python + ML, or RAG.Commit to a 2–4 week sprint (do not switch halfway)
Schedule three sessions per week.
Each session is ~60 minutes:10 min read
35 min practice (SQL query/notebook / small build)
15 min write a short note (“what I learned + what I’ll do next”)
Ship one visible artifact every week
Pick one format:a note (Notion/Doc), or
a notebook, or
a GitHub repo, or
a short write-up.
Finish the mini project at the end of the track
Your goal is not “understanding.” Your goal is a finished artifact you can point to.After you ship, tighten it into portfolio-ready quality
Use the Portfolio Rubric Toolkit to score and improve your project in 30–60 minutes:
Quick links
Start here: NBD Focus Map (Free PDF)
Portfolio Rubric Toolkit (one-time)
Choose your path
Free: Start with the Focus Map and follow one track for 2–4 weeks. Ship one mini project.
One-time: Portfolio Rubric Toolkit (upgrade a project in 30–60 minutes).
Paid: Member-only deep dives, monthly template drops, and guided paths through the archive.
Full details (kept updated): Subscriber Benefits.
I will update all the available benefits and explain how to redeem them in a separate post for MEMBER, so stay tuned!
What is Non-Brand Data?
Short answer: I help you master in-demand data skills to accelerate your career.
Every data pro needs this edge.
And this newsletter delivers it.
What you’ll get from Non-Brand Data
Strategic knowledge: what actually matters in real data work (tools, patterns, trade-offs).
Actionable insights: how to turn ideas into decisions and execution.
Retention tactics: how to make concepts stick through small artifacts and repeatable practice.
If you follow the Focus Map cadence, you will finish each track with something you can reuse: a notebook, repo, or write-up.
Want an Example?
If you want to sample before committing, start with these:
SQL: #1 What is SQL?
RAG: Simple RAG Implementation with Contextual Semantic Search
Portfolio: 14 Portfolio Projects That Demonstrate Real Business Value
About me
I am not always a data person.
I don’t have a degree in computer science, IT, artificial intelligence, or data science.
In fact, my major is Biology.
Here is a picture of me working in the field of biology-related research.
I even hold a Master's degree in Evolutionary Biology, which I acquired by studying full-time at Uppsala University in Sweden.
How did that man above become a data leader in a multinational company?
Clearly, with dedication and an appropriate strategy.
Since then, I have led teams and end-to-end projects—from problem framing to model deployment—to solve business challenges and deliver value through predictive analytics for multinational multibillion businesses.
From there, I became a co-founder and data lead of an AI-powered data platform startup that aims to drive scalable AI strategies, turning raw data into actionable insights.
Alongside my work, I’m writing online to share my expertise with everyone. This has led me to collaborate with renowned publications, such as KDnuggets, Machine Learning Mastery, Aigents, and others. In 2024, LinkedIn also won me the Top Voice badge, as people genuinely listened to my data advice.
That’s why I’ll include all my insights and experiences in this newsletter, offering content that's truly beneficial for your data career.
Enough about me! I’d be keen to hear more about you!
What has been your aspiration in the world of data science and AI?
What has brought you here? What challenges are you facing?
I’d love to hear your story! Just hit reply and share it with me.
I genuinely read and respond to all my emails. I’m delighted you subscribed, and I aim to surpass your expectations in supporting your data career.
So I can’t wait to chat with you.
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