Too many mistakes in the lectures and the main lab. Confusing for new learners when the math is wrong or the python syntax is wrong. Anyone who rates this above 3 stars you are simply not paying attention to the myriad of mistakes.

HOW IS THIS COURSE BEFORE DATA VISUALIZATION??????????!!!!!!!!!!!!!!!!!!!!!!!???????????

Honestly, I'm not sure why this course has such a high rating. I feel like it can't possibly be a reflection of what actual students felt about the course. Reading the other reviews, it's clear some of the issues people had with the course were not the course-designers fault. But, there were some tissues that are simply inexcusable. For example, typos in the lectures (especially towards the final week) show little to no proofreading was done. A lot of the labs involved "Warnings" that the instructors didn't explain to students (and so obviously some students got confused by them, even though they were inconsequential). And the final peer-graded assignment was a complete mess. The first few questions are numbered Question 1, Question 2, Question 3, etc. But the last 4-5 questions are not numbered making it very annoying to upload screenshots for each question. The directions in the assignment were simply wrong. For example, one of the questions didn't even have a prompt, just an empty text box. Someone asked about it in the "Discussions" and a staff member replied but it was never fixed in the assignment.

Trying to put the typos and logistical confusion aside, the course material was oddly organized and students were never really given an explanation as to why the concepts taught were being taught in this way. My least enjoyed course of the whole specialization.

Ton of errors, both minor and major, in the videos and the quizzes. For example, saying the a difference between two variables is significant because p > 0.05. I report them all and I've stopped counting.

Not professional at all.

Very interesting. Very good taught.

This is my first course that i completed, and i am very glad to do this .

thanking you for giving me this opportunity to enrolled this course

i learned a lot of new things from this course this was very fruitful for me.

the slides was nicely represented and the way of teaching was so amazing

i am very very thankful to all the Coursera Team

This course is very informative and good for beginners.Exercises are very useful.

I am very happy to have taken this course, I have learned a lot and gained experience thanks to IBM and Coursera

This one was a little more difficult than the previous ones.

Great Course. It took some time to be finished but it 100% worth

No Doubt COURSERA is always best AND MNC like IBM,Google courses associated with coursera are MIND-BLOWING.

The Instructors are so great at Explanation Part that hardly anyone won't Understand All the Topics

I would love to thank all the INSTRUCTORS who created such a Awesome Content for us.

My Personal Ratings For All the Instructors: 100 / 100

Just that some of the questions asked in videos were inappropriately timed, often at middle of sentences and words of the narration.

very good. I will continue.

Good course to start with. Course deals with basics of Python, Descriptive Analysis, Exploratory Analysis and Modeling.

Awesome

It would be nice if teaching staff could correct notified errors in quizzes.

Very informative and comprehensive course!

Really great overview. Outlines how to create an example predictive analytic from tart to finish in a really cohesive way.

simple and useful

Really nice course

Awesome. A must take course very handy at giving the foundation of data analysis with python and what a nice introduction to linear regression with the library sklearn. For more it looks more like an in-depth course in linear regression. Kudos, the explanations of concepts were well approached.

Great

zaebis

Amazing content.

Good program for new Learners, thank you.