I spend a lot of time learning. I've put together a list of some of the best learning resources on a number of topics that I've found most useful. I've focused on the single best resource for each topic, rather than overwhelming people with endless lists.
Software
| Subject | Resource | Notes |
|---|---|---|
| Python | The Python Learning Track on Exercism.org | I've worked through many books and courses on Python. I think this one might be the best. There's something about the way the lessons are structured, where prerequisites are clearly delineated, that makes it easier to understand and integrate. Exercism offers courses on many programming languages, not just Python. |
| Numpy, Pandas, Matplotlib | Python for Data Analysis, 3E | Similar to the previous entry, this is a nice, comprehensive work on fundamental data analysis tools like numpy, matplotlib, and pandas. Just read this one book and forget everything else. And it's free! |
| PyTorch / ML Fundamentals / Jupyter | fast.ai | The legendary fast.ai course. All of the top AI labs, like OpenAI and Anthropic, have their new hires work through this course. This is the course that took me from zero to actually being able to push machine learning projects to completion. |
| Linear Algebra | Linear Algebra and Its Applications, 5th Edition | In machine learning, the best practitioners have a deep, low-level understanding of how these systems work. This book, recommended to me by Balaji, is a great tool for doing just that. |
| Neural Networks | Neural Networks: Zero to Hero | A hands-on lecture series by Andrej Karpathy on Neural Networks. I've heard this described as "the most high leverage thing you can do" if you want to get into AI. After having worked through it, I agree. |
| Cryptography | Cryptography I | This Stanford course is widely regarded as the best free online course on cryptography. |
| Computer Science Fundamentals | Nand2Tetris | This is a classic "bottom-up" approach to computer science, which begins with logic gates and works its way up the stack. This is the most abstract resource on this list. If you just want to begin writing code ASAP, then you may deprioritize this. But if you want to dig deeper, this is essential. |
Hardware
Hardware is trickier. Everything I've learned came from firsthand experience.
The main difference between software and hardware is that there are no real consequences for failure in software. If you code doesn't compile, just debug and try again. If you mess things up too badly, you can always git revert. As such, software favors a rapid, iterative development style.
With hardware, failure often means ruining a valuable piece of equipment. Burning up a servomotor by miscalibrating the power supply is practically a rite of passage. As a result, hardware favors more up-front planning. "Measure twice, cut once."
At the most foundational level, hardware requires a certain level of hand-eye coordination that's difficult to teach. I took this for granted until I interviewed a technician candidate that couldn't handle a screwdriver without dropping the screw a dozen times. I don't know how to teach this any other way except experience.
I acquired basic tool competency from a childhood spent building and fixing things. Advanced tricks (wiring, soldering, electrical work, avionics, etc.) came from on-the-job experience at a drone startup. To anyone looking to learn, I recommend that you find a way into a workshop any way you can. Your rate of learning will be at least an order of magnitude higher than consuming online content.
If that's somehow unavailable to you, I recommend getting access to a 3D printer and just making things. Past the initial investment, each marginal print is very cheap. This permits an iterative approach to building that is forgiving of mistakes. Start with pure 3D-printed structures, then begin integrating electronics for more advanced projects.
| Subject | Resource | Notes |
|---|---|---|
| CAD Software | CAD Basics in OnShape | There are many CAD programs out there. OnShape is the one I've used most, both professionally and personally. This course will teach you to build your own parts. |
Humanities
| Subject | Resource | Notes |
|---|---|---|
| History | The Story of Civilization, by Will and Ariel Durant | I slowly worked through this eleven-volume set throughout my twenties. The experience left me with an appreciation for just how massive the world is - despite its immense size, the books gave me the feeling that this was just a brief skim over a much larger body of knowledge. |
| Futurism | Fanged Noumena, by Nick Land | Nick Land's magnum opus. It's incredible how much he predicted about the future all the way in 1991. Always divisive, Land refuses to be ignored. |
| Science Fiction | Snow Crash, by Neal Stephenson | It's impossible to narrow "good science fiction" down to a single author, much less a single book. Even so, I must put forth Neal Stephenson. I cannot think of another science ficiton writer whose work has been more prophetic. Begin with >Snow Crash |
| Philosophy | Nicomachean Ethics, by Aristotle | The older I get, the more I believe that virtue ethics is the only form of philosophy that matters. Everything else is entertainment. |
| Literature | The Complete Works of William Shakespeare | No surprises here. If reading them bores you to tears, try a live performance or, failing that, a good film adaptation. For me, the difference is night and day. |
| Art | Drawing on the Right Side of the Brain, by Betty Edwards | There are countless books that study art, but for actually producing your own works, I haven't found anything better. It ignores technical minutia and focuses entirely on teaching the reader to see the world around them. This ability to deeply observe has had significant carry-over effects to other areas of my life. |