pros:very easy to understand, even the statistics knowledge

cons: incomplete python sentences in the video require extra efforts to undertand, such as no previous sentenses for an object (i.e. x_data)

Thank you very much to the instructors. I liked the course but it could have been better designed. More exercises ascending from easy to hard & real and teaching quiz questions would make it perfect.

Great course to learn the basics for Data Analytics using Python.

I really liked the framework and data analysis template or process given in the labs. I will use them as a reference for my real job!

Really interesting course, if one wants learn programming language. Well designed and structured. Only suggestion is, if the small videos contains example that be really great to understand it well

Very good course that goes straight to the main topics needed to work on data analysis using Python. This will kick start my learning process which will be followed with a lot of coding practices.

Good course, sometimes moves a bit fast in the final modules and the labs are quite tough but great course and would recommend to broaden your knowledge of coding, data analysis and visualisation

Although good to learn the know-how of basic data analysis techniques, the quizzes are predictable and you don't end up coding as much as you should.

A good starter course to wet your feet in DA!

Very clear and easy to learn. The lab helps a lot, it gives me an intuitive instruction of the class. But some of the points seem too shallow, hope the course could provide some deep knowledge.

Good Course. Very good overview of Python libs -Pandas, Numpy, Matplotlib, Scipy, Scikitlearn and Seaborn. I really enjoyed learning about them and seeing the usage. Highly recommended course.

Totally overwhelmed with the course contents and easyness in teaching. The course will make you familiarize the fundamentals in a way that you will never forget when you used in a real world.

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.

Beginners must start from this course as it will provide the basic insights regarding Data Analysis and will prepare the learners towards advancement in a well-mannered comprehensive way.

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.

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.