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I learned a lot about algorithm concepts.

Sigh... I shouldn't have included the keyword "algorithm"... This is really... Honestly, isn't this too much... As the difficulty increases towards the end, the supporting content is way too shoddy. Even if you're going to half-ass it, there should be limits... This is really too much... Moreover, some of the video materials are missing algorithm solutions. I seriously wonder if it's okay to charge money for this... It's that bad...

I listened well.

It feels like the instructor has taught many other people. Firstly, the algorithm lecture order feels the most correct. Thank you for the good lecture.

Very good

I'm trying to study algorithms properly, so I'm taking a lecture that focuses on concepts and is aimed at beginners, but it's not a lie, it gets harder as it goes on. The explanations are poor, so I don't understand, but I just do it, solve it, and it's over. Is this the right way...? There were many times when I didn't understand the lecture and used other blogs or GPT to understand it. It feels like that's more helpful than taking this lecture.

I was impressed by your explanation of how exhaustive search, recursion, and DP are connected in the thought process. I think the advanced lectures are suitable for starting to prepare for coding tests because they cover frequently occurring types that are good to study separately. Something that would be even better is if you could provide a list of more problems to practice, which I think would help with internalization. I haven't completed all the lectures yet, but it would be great if you could share a list of good problems to apply what I've learned!

When solving algorithm problems, if we say you go through some idea -> implementation, this lecture seems to be trying to teach 'how to think about ideas' and 'what order to think in'. However, while thinking about ideas and implementing them aren't completely separate, the proportion covering implementation seems to fall short. I don't know how my thoughts might change after listening to additional parts, but I felt like the intermediate steps were lacking. The flow and ideas explained in the lecture are definitely good, and if you just take those parts, it's a good lecture, but I think it's insufficient to start and finish with just this one lecture. ++ It's difficult to listen to when you're first starting. You'll probably need to use AI in parallel as well. However, I think you need to focus on 'the content it's trying to explain'. If you focus on the content it's trying to explain and fill in the rest through other methods, it's definitely a lecture that can save you a lot of time.

It's good, but there are many parts that are too harsh here and there. I think I wasted too much time trying to understand it as it was in the lecture. I wish you would explain the code a little more sincerely.