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.

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.

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.

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.

Good but in the end of the course specially week 4 and week 5, speed of information providing in videos get to very high speed comparative to other weeks information.

For a Beginner data science ,the entire course is very helpful.Though some portion of the course needs more clarification about the topic,but overall I am satisfied

The course provides a complete guide for beginners to start data analysis. but mostly it provides a rough overview of concepts so we need to learn in detail manually

Some of the topics at the end of the video have been rushed to end. I would rather liked to see an elaborate examples for those topics to atleast have an idea of it.

185/5000

It requires more technical skills and knowledge in other areas not mentioned like python or IBM platform.

However this has done push me to learn more skills.

I could have used a little more explanation when it came to Pipelines and Polynomials, but I figure there will likely be more of that to come in the later courses.

The course is a good start for beginners. The course contained everything useful form churning of data to regression. Pretty decent explanation with practice labs.