Python A-Z™: Python For Data Science With Real Exercises! (Udemy.com)

I really liked Kirill as the instructor. He explains concepts clearly and keeps the material engaging. Although the course is labeled as a Python course, it leans heavily toward data science applications of Python, so I would consider it more of an advanced course rather than a general Python course. One thing I wish the course included was instructor-led walkthroughs of the homework sections. Seeing Kirill solve the exercises would have made the learning experience even better. Overall, it's a solid course, and I'd give it an A.

> Great Python course overall. The content is well-organized, practical, and easy to follow, and the instructor does an excellent job of explaining concepts clearly. I learned a lot and felt the course provided a strong foundation in Python. The only minor issues were that some homework lectures felt a bit slow and were occasionally difficult to understand, and a few examples are slightly outdated due to package updates since the course was released. Despite these small drawbacks, I would definitely recommend the course.

I chose this course because I am redirecting my career towards Datascience. This course covers the basics to be able to analyze data in Python, as well as presenting conclusions in the form of compelling graphs. It is great that this is a hands on course: if you take it, choose the follow-along style, so the lectures sink in even deeper and you start getting Python in your fingers. The examples are great too: you'll have plenty of time to get bored with dull data, after you explore high level sports, world demographics, and movie producing numbers during the course. The best aspect of this course is that, being Python as extensive as it is, this course has a big component of "learning to learn", by providing hints and leads on how to explore on your own the parts that a finite course can only discover to you, so you are fit and equipped to broaden your knowledge on your own. With this course, your Python journey through data analysis and visualisation has only begun: it is up to you to keep walking.

I fully recommend this course! 1. The concepts were easily digestible. Each section taught a specific concept. 2. The format of the course was excellent. The instructor went slow enough to follow. Every section built on the previous section. 3. The data sets were very intuitive and interesting. Basketball, movies, etc. It was really fun to dig into the data sets. 4. Lastly, Kyrill was a great instructor. his explanations were clear. He often suggested new things to try without losing focus on the topic at hand. However, several issues: 1. The instructor teaches things one way. However, the homework solution often uses an alternative approach. This is not good because it makes the students notes confusing. 2. On the last sections, a just a few key concepts were left out of the class. Then, the homework used these key concepts. So, the students had to google the concept. Again, this makes the notes confusing. The teacher should have just taken 10 extra minutes to cover all the key concepts in class. That way the student would have been fully prepared for the homework. 3. The later homework explanation were lacking. Some of the concept used to solve the homework were not fully explained. Overall, these are minor issues. This is a great course. I fully recommend!

Great, just like every Kirill course I have taken before. I did this one as a quick course to review the base knowledge and reinforce the basics of Python in Data Science and it was great, even thinking I know the content I learned new things.

Maybe this course is good for the complete beginners, but if you already has some experience in Python - for you that course is going to be extremely simple. It covers only the very basic tasks and definitely can't be called "Python A-Z".
Mostly I came here for plots and diagrams and I got a pretty good examples, but I was hoping for deeper digging into either possible ways of visualisation (regressions, histograms, animated charts, different types of jointplots etc) or explanations of what charts are usually used for different particular tasks.
It is also a big lack of selftraining here - home tasks are all almost only ctr+C / ctr+V, there was no need to investigate or invent something, just copy examples with the couple of changes (names, columns). Basically there is even a full explanation where you mostly only have to fill gaps. I was doing it without following the video - it's still too simple.
To sum up - it was useful to get the basic view on plotting, but it's only 1/3 of a course. If you have some experience in coding - nothing to do for you here. If you don't - I would recommend to find something else, because, to be honest, I doubt that this course can give you a complete understanding of Python structures and principles.

Excellent teaching, never thought coding is this fun

Course can be updated with more exercises and homeworks.

This is really very good course for people who looking for phyton for data analyses.

Interesting and useful. Solution should be placed just after the challenges just to make the course more streamlined. All in all I'm very happy with the course.

It is a great course. The teacher is gifted. However, I am not sure whether someone with little background in programming would have the same opinion. If these people are among the intended audience of the course, it should contain a much larger set of small and middle size exercises, which are easy to introduce.

Course was interesting and very relevant. Enjoyed thoroughly.