This was a comprehensive course which dives deep into data analysis. The visualization part could still be improved, but nothing to take away from the course. It is one of the best out there.

It will be helpful if a video is added on:

1) how to store multiple results from different models in single dataframe

2) how to automate the process. More example needed on Grid and Pipeline.

Great course, you can understand in a general way the use os Python to analyse raw data and organice it to create a better model. However I couldn't use in a proper way the external tool.

Pretty good overall. Among drawbacks - too much already written in assignments. Also the functions are mentioned very very briefly, no explanation on parameters, on possible deviations.

Theory and examples are good. Suggest having full and complete Python course code with more examples of each coding. So we can get more ideas and understanding of the Python environment.

The course was truly informational. The labs and cheat sheets were really helpful. Just a few videos could have been more descriptive instead of leaving their explanations for the labs.

Questions while listening to lessons in some of the lectures are coming before theory explained by the teacher .Better if question is at least 10 seconds after related theory explained.

Los temas tratados son muy útiles y se desarrollan de gran manera. El herramienta de LAB es la más completa del curso. Considero que se puede aumentar la rigurosidad de la evaluación

This was pretty good, I think maybe the best in the IBM machine learning certificate. I took Andrew Ng's course prior to this, so to watch python sklearn in action was a real treat.

It is a good course for beginners but I feel that the quizzes could have been a bit more challenging. And if the codes were executed in the Python domain , it would have been nice.

Everything felt just a little too easy. I have minimal Python skills and nearly failed college statistics, but I never had any trouble here. The exercise notebooks were fantastic!

Very interactive and informative content.Covered all the data analysis related concept. I would suggest that spare some more time on Regression techniques to details information.

I thought this course was very informative, but there were some typos and I thought some of the concepts were introduced too quickly without links to previous or upcoming ideas.

Good content through out the learning, the lab notebooks are great resource to do the Hands on by ourselves. Includes each corner of the analysis methods. Good foundation course

This is a very useful and very appropriate to those who want to pursue their career in Data Science.

Me as an data science enthusiast liked the course, and would also recommend.

Course provides a good intro and the visuals are great. It doesn't however go deep into each topic and doesn't provide enough examples to explain concepts for different cases.

There were some statistical concepts in Week 4 and Week 5 which were difficult to grasp for a beginner like me.

More in depth explanations were required which were missing.

Great course. especially on the final assignment and as a new learner without any basic knowledge on python skill. it took me quite a while and challenge to get it complete.

I really liked the course overall.

I expected a bit more depth in the final, but the class material was gold.

Best breakdown of the Chi2 I've come across, very easy to follow.

Would be a bit hard for someone who hasn't got a background with math and statistics knowledge. Not very much explanation. Also, not much interpreting for the methods used.

Pretty dry material. Hard topic to teach since the process really comes from experience. Could stand to focus a bit more on ways to explore and clean data. Not bad though.

The lab is good for learning, the quiz i think should be add more questions, too small, overall is ok for the beginner for learning the data analysis with Python, thanks.

very good course, it's getting harder in W5,6 and it was hard to understand, I think that the instructor could be more informative about topics discussed in these week .

Good introduction to the things one can do with Python and Pandas, but overall fairly basic and does not require the students to actually program something of their own.

Good for a first course in data analysis however this course covers the subject on a very superficial level. There are a few errors in the assignment's solution guide.