Classes in IBM Data Analyst track seem to be for marketing purposes. They force you to sign up for IBM products, provide your personal information and credit card number, and then it doesn't even work. You really don't learn much in the actual classes, they just seem to want to advertise IBM products.

Absolutely worthless course. Waste of time. You will only get begginner knowledge after listenin to videos with tedius useless information. I knew python before and i watched in horror and disgust how horrible topics were covered and how unnecesarily complicated they were forced to become.

Examples in the videos was not good, at least giving some examples for necessary functions in videos would be good, If you don't want to put new videos than at least give students the documentation link to guide them so they can learn themselves with parallel to labs.

Plenty of essential stuff has been skipped. There was no consistancy and unfortunately it didn't go gradually. I wish the authors assumed that this course has been developed for beginners i.e. people who probably see all of this stuff for the very first time.

Signed up for Applied AI and suddenly IBM and Coursera decided to update the program to AI Developer program. Thumbs down, I only committed my time for 7 courses, but now you added 3 more courses and I can't continue anymore. Wasted my time big time!

It all makes sense till about half way into the course then it turns into some kind of gibberish and you get completely lost. The videos are just text to speech and the labs are very bland and not interactive at all. Waste of time and money.

The entire Data Science Certification course is misdesigned. It is not at all beginner-friendly. It seems like the entire thing is rushing down on covering the concepts within 5-10 minutes of videos with insufficient demonstration.

You won't walk away with anything more than a superficial understanding of Python. The introduction is cursory, the course breezes very specialized python code for data science and there is very little hands-on practice.

One of the worst courses/attempts at teaching something I've ever seen. Datacamp Python is a million times better and this random book I bought was way better.

Labs are garbage (only half of them load, most of the info in the lab is not covered by the video, we don't use an interpreter), videos are too fast

Weeks 1-3 were really good, But the lessons in weeks 4-5 were really were incomprehensible and it was really hard to understand things

Trash. Have someone who knows how to put together a course rewrite this. The ordering is wrong and it skips steps. Very bad.

It should be much more better explained for a true beginners. Also, there are many corrections needed.

Pretty disorganized. It did not seem like staff were experts. Lots of mistakes in the code.

A lot of not-working codes and tasks unable to solve based on the lessons taught before

Lab is not working. I am not able to access any of the hands-on lab exercises.

Python for beginners... it teaches nothing about data or AI or development

its very bad, not clear and the videos doesnt explaine any thing.

Lots of ambiguous statements, and sometimes inconsistent content

very poor course fuck off coursera

worst python course ever

assignment problems

Labs don't work

Very very basic

I recently joined the "Python for Data Science, AI & Development" course as part of the "IBM Data Science Professional Certificate" specialization on Coursera, and I am thoroughly impressed with the quality and depth of the content. This course is a fantastic introduction to Python, especially tailored for those interested in data science and AI development. The instructors did an excellent job of breaking down complex concepts into easy-to-understand segments, making it accessible even for beginners. The hands-on labs and assignments were particularly beneficial, allowing me to apply what I learned in real-world scenarios. The Jupyter Notebooks provided a practical environment for coding, which helped reinforce the learning experience. I appreciated the comprehensive coverage of Python libraries such as Pandas, Numpy, and Matplotlib. These tools are essential for data manipulation and visualization, and the course provided clear, practical examples of how to use them effectively. The integration of AI topics added a unique dimension, highlighting Python's versatility in this cutting-edge field. Overall, the "Python for Data Science, AI & Development" course is well-structured, engaging, and highly informative. It has equipped me with valuable skills that I can apply in my current projects and has significantly boosted my confidence in using Python for Data Science and AI Development. I highly recommend this course to anyone looking to enhance their programming skills and dive into the world of data science and AI.