I usually don't comment on bad reviews, but I think this review is excessive, so I'm responding. First of all, R is as important a language for data visualization as Python, so I explained it here and there for those who need it, but I don't know how much time was spent to make such a comment. Also, Anaconda is a software used not only in this lecture but also in most lectures on data analysis using Python, so I don't understand why you're taking issue with it. This course is a beginner's course, so it doesn't cover virtual environments, but it's covered in other advanced project courses, and I can't agree with the fact that it talks as if a virtual environment is essential. I excluded it because I thought it would be confusing in the basic course, and you can learn the content of the course sufficiently even without a virtual environment. Each lecture has its own purpose and level. This course covers data visualization and manipulation with Python. There are separate courses that cover TensorFlow and machine learning. It's clearly stated in the lecture title and introduction, so I don't know why you're complaining that it has nothing to do with the course and that you can't learn TensorFlow. Looking at the student ID, I saw that you left similar negative reviews and low ratings for my previous 'Python 100-Minute Core Course', so I don't understand why you are taking my insufficient lectures repeatedly and leaving such reviews. No matter how many different perspectives there are in the lectures, I hope you will be careful when making your reviews, considering the position of the instructor who worked hard to create the lectures, and the lecture topics and purposes.

Simply put, beginners don't know anything. They have to teach everything. So they watch the lecture. However, the lecture only works in a specific environment. Beginners think, "Huh? My environment is different. What should I do?" and give up or search the Internet endlessly. If this happens, isn't there no reason to pay for the lecture? The reason for paying for the lecture is to save time and effort by searching for this and that. However, the part that must be mentioned in the lecture, such as installing the package with pip... (Pandas, which appears here, can be installed by just pip install pandas, but if you look at the lecture content, it says to go to the Pandas homepage and install it yourself if you want to install it individually.) What should subscribers who have development boards that are not supported by Anaconda (such as NVIDIA's Jetson Nano board or even Raspberry Pi) do? Just install Anaconda... This kind of thing... I know it all. It's convenient if you install Anaconda. The problem is that there are environments that do not support Anaconda. Especially if the CPU is ARM series. Linux series only supports x86_64 series and IBM Power9 (if you look at the Anaconda website download). In addition, if it is truly for beginners, it is natural to mention virtualization, so that later subscribers will think that they should try using such technology. I think that the more beginners are, the more necessary technologies should be mentioned at least once. R You could mention it. But you didn't mention virtualization, which is a really necessary technology. If it is a Python course, you should focus on Python first. Wouldn't it be more reasonable to suggest virtualization or an installation method using pip when mentioning R? And to download the materials needed for the course, you have to sign up for a site created by the instructor.. I guess that's because it is a free course. However, since it is a paid lecture, I wonder if having to sign up for another site to download the materials needed to watch this lecture and practice is a trick to increase the number of members of the site operated by the instructor. (For reference, when you read books, there are cases where you have to download source code or materials, but most of them are downloaded without signing up.) I feel very sorry that I have to provide my personal information to the instructor to download the materials for the lectures I pay for. I don't think this is a fair action that an instructor who makes money through paid lectures should take toward subscribers. Finally, while watching the lectures, people keep asking why I keep writing bad reviews... I want a refund too. But at first, I paid for all the lectures (6 lectures from Python Basics to TensorFlow). I watch them when I have time because I feel bad about wasting money. And it's called a bad review, but I didn't just write, "This lecture sucks." I wrote down the reasons, but rather than thinking about correcting them after seeing them, it's a shame to express my dissatisfaction by calling them bad reviews. The purpose and level are good words. However, even for beginners, there are some parts that are absolutely necessary. Just as the instructor thinks that R is worth mentioning, I think it's like installing using pip or virtualization. I think it's putting the cart before the horse to mention R, but not mentioning one of Python's core functions, installing using pip, and virtualization. I'm not asking you to explain virtualization. Just mentioning it like you mention R would be a huge help to beginners.