I'm a high school freshman with a basic understanding of Python—just enough to pass the USACO bronze. I've started watching CS50x and am currently self-teaching calculus, planning to move on to linear algebra next. I've heard good things about MIT's 6.034 course but I'm concerned it might be outdated since it's from 2010. I'm looking for step-by-step guidance to build my knowledge from a beginner's perspective, including specific courses and resources. Ultimately, I'm aiming to conduct meaningful AI research by this summer. Additionally, I'd love to learn about software product innovation since it could be fun to start a project while learning.
2 Answers
You're in an awesome spot as a freshman! Here's a simple path I suggest:
1. Get really comfortable with Python—focus on functions, data structures, and OOP.
2. Complete CS50x to nail CS fundamentals.
3. Learn linear algebra and basic probability. Don’t worry about mastering calculus right away.
4. Find a practical machine learning course and start building small projects.
5. Before diving into research, try re-implementing basic models.
MIT 6.034 is solid, but right now the focus should be on fundamentals and hands-on practice. Aiming to replicate existing work or make small improvements is a great goal for your research by summer. And for product innovation, start building early; the experience will be invaluable.
Don't stress too much about the age of the course material. A lot of the fundamental concepts from AI and calculus have remained consistent over the years. Think of it this way: you’re learning calculus, which dates back to the 1600s! What matters is that you grasp those core principles. The best way to learn programming is to actually write code. Dive into projects that interest you, even small ones to start with!
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