Let me start with a confession: I’m not a huge fan of newsletters. I’d much rather go out and find what I’m looking for than have my inbox cluttered with unread emails every week. For a while, I subscribed to dozens, but the constant notifications just got annoying. Now, I only keep a few absolute gems and aggressively unsubscribe from the rest.

I'm a visual learner, so I spend a lot of time on YouTube, and I'm constantly amazed by the incredible, high-quality resources available for free. That said, we live in a new world. These days, Generative AI and LLMs are an insanely powerful source of knowledge. Tools like ChatGPT, Claude, Perplexity, and Google's Gemini can be fantastic tutors, explaining complex topics on demand.

But sometimes you need more than a chatbot. You need specific information, and especially, you need opinions. For that, Reddit is an underrated goldmine for finding specific information and candid reviews. And for deep-dive tech articles, Medium is packed with gems. Its publication Towards Data Science was an absolute game-changer for me. I'm not joking when I say that before LLMs were a thing, I probably spent most of my days at university just reading articles on there.

So, this isn't a generic list. This is my personal, opinionated guide to the resources that have genuinely helped me.

AI & Deep Learning: Where to Begin

This field moves at lightning speed, but the fundamentals are timeless.

Andrew Ng's Courses on Coursera

Let's get this out of the way. Andrew Ng is THE guy that made me (and honestly, most of the industry) truly interested in Machine Learning. His ability to explain complex ideas with simple intuition is unmatched. His Machine Learning Specialization is where my passion sparked. If you're starting out, start here. It's almost a rite of passage.

Andrej Karpathy's YouTube Channel

Once you have the basics, go straight to Andrej Karpathy's YouTube. His "Neural Networks: Zero to Hero" series is pure gold. He builds neural networks from scratch in Python, explaining every single line. His videos provide an incredible depth of knowledge on LLMs and are surprisingly easy to grasp.

Lex Fridman Podcast

This podcast is A MUST. Lex's interviews go far beyond tech, touching on philosophy, politics, and the human condition. They are often long, but some are absolutely phenomenal and provide incredible value add. I strongly recommend his conversations with Andrej Karpathy, Sam Altman, Volodymyr Zelenskyy, and Sundar Pichai.

The "Godfather of AI", Geoffrey Hinton

I’ll jokingly say that it's worth watching any interview where Geoffrey Hinton speaks. He has a more pessimistic view on AI safety, which is a crucial perspective to hear. He recently did an interview with The Diary of a CEO and while some of his views might seem extremist, they come from one of the most brilliant minds in the field and could be completely legit and accurate. It's essential to listen to both sides of the AI safety debate.

Visual Learning Aids

To truly understand the math behind ML algorithms without getting bogged down, StatQuest with Josh Starmer and 3Blue1Brown are second to none. They make complex topics visual and intuitive.

Entrepreneurship and Venture Capital

Lately, I've become more passionate about the business and venture side of tech. If you share that interest, there's one podcast that stands out.

20VC with Harry Stebbings

This podcast is a treasure trove of insights from the world's most incredible founders, CEOs, and VCs. Harry Stebbings is a phenomenal interviewer. You can find his podcast on Spotify here: The Twenty Minute VC. I can't recommend the episodes with the former Snowflake CEO Frank Slootman, Reid Hoffman, and especially the one with Nik Storonsky enough.

Data Engineering

While AI gets the headlines, data engineering is the backbone that makes it all possible. There are great influencers on LinkedIn, but my absolute favourite is:

Zach Wilson (DataExpert.io)

Zach provides immense value through his content. He offers incredible courses at DataExpert.io, including a free course to get you started. His approach is practical, modern, and highly relevant for anyone looking to build a career in data.

Final Thoughts: Knowledge is Your Moat

It's easy to get caught up in an endless cycle of tutorials. The most important thing is continuous and PRACTICAL learning. Build things. Break things. Get your hands dirty.

That said, knowledge is still key, especially in an era where hard skills like coding are at risk of being commoditized by smarter LLMs and agents. Understanding the why behind the what is your ultimate competitive advantage. Build a strong foundation of knowledge, stay curious, and you'll be well-equipped for whatever comes next.