Edited
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Reviews 7
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Average rating 4.3
I chose this lecture because I thought I could get an overview of LLM, LangChain, OpenAI, Model Context Protocol (MCP), LangSmith, LangGraph, etc. all at once. However, now that I've finished the lecture, I'm not sure what has stuck in my head. Even though I've been working as a full-stack developer for almost 10 years and have a shallow knowledge of AI, I personally feel that the knowledge transfer technique of this lecture doesn't suit me at all. It might be okay for someone who is suited to the style of lecture that just "reads straight through" from beginning to end, but the further I went, the less I understood what was being talked about. I didn't think much of the fact that the lecture materials were in English when I first chose this lecture, but because things that are hard to understand even in Korean were just written in English without detailed explanation, reading the English with my eyes and listening to the Korean with my ears was very tiring, and I felt like the knowledge itself wasn't sinking in. If the goal was to include English knowledge to help with overseas employment, it would have been an easier lecture for the listener if only the terms were summarized in English and the knowledge itself was explained fully in Korean. When I first listened to about 40%, I thought it was my aversion to English, but now that I've listened to 100%, it seems the biggest reason for wasting my time and money was that the lecture technique itself was nothing more than just reading straight through. I was going to give 1 star, but seeing that a lot of effort went into preparing the lecture, and thinking that it might have been a lecture that could convey a lot of knowledge to someone who can learn just by listening to things being read straight through, I gave 2 stars. However, I do think I might revisit it someday when specific knowledge is actually needed... but I personally believe that just reading something straight through constantly is different from "teaching knowledge," and from a teaching perspective, it's a lecture I cannot give a good score to.
Hello. Thank you very much for leaving us valuable review and detailed feedback. First, I am very sorry to hear that you felt disappointed that the lecture did not meet your expectations. I have read every point you made carefully, and I take the part about the "knowledge delivery method" especially seriously. I also agree with your perspective on LangChain. LangChain is closer to a template or abstraction tool for efficiently utilizing LLMs rather than a tool for creating specific complete services. Therefore, the lecture was structured to focus on understanding the roles and concepts of various components rather than immediate practical application. However, I feel that improvement is definitely needed regarding the fact that this process didn't feel tangible in practice and that the delivery method was one-sided and caused fatigue. Thank you also for your important feedback regarding the English content in the lecture materials. The intention behind writing it in English was to help those considering a global career in the long term, but I deeply agree with your opinion that while English terms should be introduced, the knowledge transfer should have been thoroughly explained in Korean, as you mentioned. Despite the shortcomings of this lecture, your generous assessment that the effort put into preparing the class could still be helpful to some users is a great comfort. Going forward, I will work to improve the delivery method and language composition so that students from more diverse backgrounds can understand clearly and easily. Thank you once again for your heartfelt feedback.
