one year of studying (it was a mistake)
📚 Main topics
- A year of broad studyThe creator spent the past year studying math, computer science, data engineering, and machine learning after becoming bored with web development and wanting to explore AI. 0:00
- Math for machine learningThey studied linear algebra, discrete math, and machine-learning math, finding that practice-based learning built real skills but took about four months. 1:31
- Computer science foundationsTheir studies covered low-level computing, algorithms, database internals, and networking, though much of it lacked exercises or practical projects. 4:06
- Data engineering and machine learningData engineering connected most directly to their day job, and they praised Designing Data-Intensive Applications. They also explored machine-learning and deep-learning resources, while noting that PyTorch has become more prominent than TensorFlow. 6:42
✨ Key takeaways
- Watching and reading aren’t enoughLectures and books can create the feeling of understanding, but solving problems and applying ideas are needed to remember and use them. 2:02
- Learn according to your goalMath and algorithms benefit from progressing through increasingly difficult problems, while most programming skills are better learned by starting with a project and studying what it requires. 9:52
- Focus mattersStudying for several different career paths at once led to scattered effort, and most of the material did not connect to the creator’s everyday work. 10:23
🧠 Lessons learned
- Prioritize practical outputThe year produced lots of consumed information but few substantial accomplishments. Building things would have helped solidify the learning and demonstrate what they could do. 9:20
- Choose a manageable projectA good project should take about a month, stretch existing skills, and avoid becoming so ambitious that it leads into distracting rabbit holes. 11:26
🏁 Conclusion/next steps
- Make the next year project-focusedThe creator plans to center their learning on projects, while possibly taking some courses along the way, and share what they build in future videos. 11:58
Transcript excerpt
0:00 I spent a lot of the last year studying math computer science and all sorts of academic things and while this is really interesting and things that I think will be useful throughout my career I think it was a mistake it was not the best use of my time in this video I'm going to go over what I learned what I studied and most importantly what I would do next time if I could start over so it was November 2023 a little over a year ago when
0:30 I decided I was bored with web development I wanted to do something different and I thought ai ai sounds great and so I picked up a couple books this one uh deep learning so turns out it is a graduate level math textbook and I did not have the preparation for that this one is pretty great uh it required a little more math than I had that was
1:00 reasonable and uh also required uh pandas numpy a bunch of python stuff so I bounced off of that a little bit and both these together set off my journey of learning this journey lasted a little over a year and I made a lot of mistakes which you can now learn from so let's go over what I learned so uh first I learned a bunch of math and that's because I was so shocked when I read these books that I was like wow there's
🔒 The full, searchable transcript is available with Pro.
Questions & Answers
Common questions about this video
¿Por qué el narrador considera que estudiar durante el último año fue un error?
¿Qué problema encontró al aprender matemáticas mediante cursos y videos?
¿Qué pensó el narrador sobre aprender matemáticas para trabajar en ingeniería de software?
¿Qué habría hecho distinto si de verdad hubiera querido aprender programación CUDA?
¿Por qué le gustó la hoja de ruta de NeetCode para aprender algoritmos?
¿Qué recomienda para aprender la mayoría de los temas de programación?
¿Qué enfoque piensa seguir el narrador durante el próximo año?
Related summaries
Samsung S26 Ultra - Best Camera Settings for Video and Photos!
How did a few hundred Spanish soldiers topple two empires? – Si Sheppard
Sarah Paine — Why wars are so difficult to end
as maiores novidades em AI
Deep Dive into LLMs like ChatGPT
