📚 What I’m learning for 2027

I’ve been working in software and data science for over 8 years, but lately I’d be lying if I said I wasn’t a little worried about where our jobs are heading. 😅

The future feels more uncertain than ever, so I’ve been thinking seriously about what’s actually worth learning to stay relevant in 2027 and beyond.

I searched around for resources I’d personally want to invest my time in, and i figured why not sharing with you guys as well. This is my shortlist 👇

🧠 1. Let’s Build GPT from Scratch, Andrej Karpathy
Build a GPT yourself and finally understand what’s happening behind the API.
⏱️ ~2h
🔗 https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ

🔥 2. Neural Networks: Zero to Hero, Andrej Karpathy
A deeper dive into neural networks, backpropagation, language models, GPT and tokenization.
⏱️ ~19h
🔗 https://karpathy.ai/zero-to-hero.html

🤖 3. Hugging Face AI Agents Course
Learn how AI agents actually work: tools, actions, reasoning and agentic workflows.
💰 Free
🔗 https://huggingface.co/learn/agents-course/unit0/introduction

🏗 4. Designing Data-Intensive Applications, Martin Kleppmann
The classic for understanding databases, distributed systems, replication, partitioning, streams and designing systems that scale.
📖 ~600 pages
🔗 https://github.com/aasthas2022/SDE-Interview-and-Prep-Roadmap/blob/main/System%20Design/Resources/Designing%20Data%20Intensive%20Applications%20by%20Martin%20Kleppmann.pdf

⚙️ 5. Made With ML
The production side of ML: deployment, testing, monitoring, data pipelines and MLOps.
💰 Free
🔗 https://madewithml.com/#course

🎯 Why these?
My bet for 2027 is that writing code itself will become easier, while understanding AI + production systems + architecture will become even more valuable.
So that’s what I’m focusing on.

If you know a resource that belongs on this list please share it so everybody can find it valuable.

Hope this helps ❤️