Python Data Science with Pandas: Master 12 Advanced Projects (Udemy.com)

This course is well-suited for beginners and provides a solid foundation in data exploration using Python pandas. While I appreciated the use of straightforward datasets for learning purposes, I was expecting to work on 12 distinct projects. However, many of the 'projects' were different parts of the analysis of the same dataset. Additionally, I was hoping for more advanced insights, such as comparisons of different methods for completing tasks or discussions about how these concepts apply to real-life projects.

It's a very good, well organized course. After finishing some courses in Data Analytics with Python and learning so much stuff I was left confused. I learned a lot but didn't know what to do with all those information. Well, it's not the case any more. Alexander's method for the projects not just teaches you new methods in Pandas it also gives you a solid understanding of what it's really like working on a project. The road map of Data Analysis. Now, I feel confident to start my own projects. Thank you Alexander for this very professional content!

From someone who has taken over 30 certified courses, including 2 Harvard courses, in an effort to fast track a new data science life path, Alexander is an AMAZING teacher. There are so many advanced Pandas classes I have been through, and NONE of them came close to how much I am learning here. And I am truly understanding all the details of how Pandas works now! Finally!! This is definitely the next step I needed to never be embarrassed for not knowing an obscure Pandas function in an interview ever again!

I am halfway through this course and I am amzed by the delivery and instructor's comprehension and grasp of Pandas. The challanges presented in this course are something definitely what I was looking for and the Alexander is very engaging and hits all the points at once.

I'm a bit more than a novice so this course was very exciting for me. It showed simple ways of doing things that I was struggling with. He has a clear and focused process for cleaning, analyzing, and teasing the data. It also showed a number of visual and other statistical commands that I had never run across before with Python. I really enjoyed this course and already have plans to use what I learned.

The course for me has been above expectations. It is truly comprehensive and the examples are very well prepared. I found the system followed also very appropriate for this kind of content. You can work at your own pace as the content of the notebook is always on sight. The explanations are really good. As a suggestion for improvement I would have liked it had a bit more explanations and examples on application of SQLite. I would also like it had a bit more explanations on matplotlib. For example I still found it a bit confusing the way in which fig and ax are used and I really struggle to find examples on the internet when I need to do something "special" on a chart (as removing tickmarks, use different kinds of lines, etc..). Lastly I would suggest as an idea for development some material on QuantLib. There is very little available.

Extremely valuable course. Since the teacher takes through the analysis line by line, and starts from basic analysis to very complex analysis in real world, it is very useful. A suggestion: There should be one project exclusively on visualisations to cover some advanced concepts.

The course material and project were extremely useful and practical. Thanks to this course I learned how to work with real cases (including managing and cleaning complex datasets). All processes and steps were clearly explained. The teacher was extremely responsive. It was a great learning experience!

The instructor is definitely very knowledgeable and did an excellent job splitting the course in cohesive and increasingly difficult sections. Nonetheless, I feel that the course is seriously missing a "self-teaching" notebook to be able to attempt the exercises on our own. Section 1 had this, but none of the other sections. The result is, you're mostly watching the instructor going through the content but since the queries are already pre-filled and the notebooks lack detailed instructions, you simply run the cells and try to understand the code on the go. it's very difficult to progress without applying. I would suggest providing a self-learning notebook for all sections with detailed instructions, so at least we can attempt the challenges ourselves.

Great teaching. Covers most of the stuff. Suggestion to others taking the course, explore more as he teaches you. Take this course if you want to learn most of the things about Pandas and how you can use it for data analysis and not for machine learning.