one year of studying (it was a mistake)
📚 Main Topics
Initial Motivation and Shift in Focus
- Transition from web development to AI and machine learning.
- Encountered challenges with advanced math and programming concepts.
Mathematics Learning
- Engaged with various math topics, including linear algebra and discrete math.
- Realized the importance of practical application over passive learning.
- Utilized Math Academy for structured learning and skill assessment.
Computer Science Fundamentals
- Explored low-level programming and hardware concepts.
- Took courses on database internals and algorithms.
- Emphasized the importance of practical exercises and projects for retention.
Data Engineering
- Applied data engineering concepts directly in the workplace.
- Recommended the book "Designing Data-Intensive Applications" for its comprehensive overview.
Machine Learning and AI
- Studied various algorithms and frameworks, noting the shift from TensorFlow to PyTorch.
- Acknowledged the need for hands-on experience in machine learning.
✨ Key Takeaways
- Active Learning is CrucialWatching lectures or reading books is not enough; practical application is necessary to truly understand and retain knowledge.
- Focus on ProjectsInstead of scattering efforts across multiple topics, concentrate on specific projects that challenge and expand your skills.
- Balance Theory and PracticeWhile theoretical knowledge is important, it should be complemented with practical exercises to solidify understanding.
🧠 Lessons Learned
- Avoid OverwhelmTrying to learn too many disparate topics at once can lead to confusion and lack of depth in any one area.
- Set Clear GoalsDefine specific projects or outcomes to guide learning efforts and maintain focus.
- Iterative LearningStart with simpler problems and gradually tackle more complex challenges to build confidence and competence.
🏁 Future Plans
- Shift towards a project-focused approach for the upcoming year, aiming to create tangible outputs and share insights through video content.
- Continue to explore and learn in a structured manner, ensuring that each new skill is applied in practical scenarios.
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
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Questions & Answers
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