I like the systematic lectures

I'm disappointed with the difficulty level of the lecture!

It's so packed with value

I'm studying hard.

I listened to the Backtest Research and Algorithm Trading courses continuously. I ran the provided code while taking the courses. As a non-developer who has only built web applications using Python web frameworks (Django, Flask, FastAPI)... there were quite a few parts that were a bit difficult for me to fully follow. Since I don't work in this field... I lack experience..., and I don't have much experience trading stocks either, so the lack of basic knowledge in both areas made it more challenging, but it was still sufficient for getting ideas. If I watch it multiple times and gradually build up my related background knowledge, something will work out. I remember when I first started coding with Python through self-study, it also took time to get on track. I hope there will be an algorithm trading course related to the Korean stock market as well. Thank you.

It seems difficult in some ways, yet there appears to be a lot to learn. Anyway, if I go, I should be able to get somewhere.

I knew that using statistics to predict stock prices was reasonable, but it was great to learn the detailed process of actually creating a program. Of course, I don't have the ability to program it myself yet, but through this course, I've gained confidence in automated trading programs for the future. I will watch the lectures repeatedly and work hard to understand them. Thank you.

This was a disappointing lecture from a developer's perspective. It felt more like I bought code rather than bought a lecture. Most of it proceeds with live coding, and there's a lot of hard coding. I suspect this might not be targeted at developers. If modifications or updates are needed later, some parts could be handled with AI, but I don't think I would be able to create such a system myself. There seem to be potential issues down the road, such as having to run it locally and the fact that individual library versions are not specified. However, thanks to this, I was able to get ideas and references worth considering. Thank you.

The architectural, financial, and course structure aspects are all disappointing. This is a case of what not to do. Advantages: Introduces convenient third-party services and frameworks. Disadvantages: The output feels like vibe coding, and most of it is just reading lecture materials that feel like they were generated by LLM. It's shocking from the start that stock names to be stored in the DB are hardcoded in columns.

It was fast, but I listened well without much difficulty. I will make sure to put it to good use in practice.