The course structure is clear. I can recall the concepts learnt in the previous chapters on this course.

The Final Assignment rubic is clear. I know what I should hand in to prevent mark loss due to misunderstanding.

Really helpful course to learn the basics of pandas and scikit-learn. The videos were easy to follow and very clear, and they were complemented well with the lab notebooks and quizzes. Thank you to the organizers! :)

As a data scientist in retail industy I recommend this course to you because this course has lots of meaningful topics and educated professors are teaching you.

Hope you the bests and enjoy learning with Coursera!

I think this course is the highlight of the Applied Data Science specialization. I learned so much and gave me the tools to learn more on my own. It was really engaging and I never had a dull moment in this Course.

This is a great course. I went away with so much knowledge on modelling and model testing. The labs are also very well structured and not just a repetition of the class presentation. I recommend this course highly.

The beginning of the course helps you understanding how you can manage your data with python. In the end linear regression, and ridge regression is also introduced. Good course for those not familiar in this field.

Excellente content and very didactic laboratory. There is a lot of information in the course and at the same time it encourages me to investigate and further develop, particularly in Model Evaluation and Refinement

Very "meaty" hands-on work with doing some data wrangling, exploratory analysis and models with single linear, multiple linear, and polynomial regression fits. I took several hundreds of lines of code in my notes.

Thank you so much for creating this is great learning and useful course that I got for Data Analytics.This course is very beneficial for all to enhance the knowledge about data analysis with Python.Thank you sir.

I find the course well organized and the lab sessions made use of relevant instruction that I can use for my daily work. The final assignment could be more challenging. Overall a very helpful learning experience.

Excellent explanation about the topics and helpful examples. Course requires reading outside the course module for better understanding. Will be helpful, if you could run the program on the window and explain us.

Extremely helpful course for those who are new to the terms of machine learning concepts are well explained and sufficient practice taken in Lab modules and the last peer-graded assignment helped me learn a lot.

A rotating three-dimensional plot may be added. Its very easy and practical to complement the analysis presented. Otherwise the course is very complete.

Also, the pipe explanation may be improved a little bit.

This course provided me with the necessary knowledge and tools to introduce me to the field of creating and evaluating data analysis models to make predictions with Artificial Intelligence and Machine Learning.

I am reviewing this course after the completing it. It was a good learning experience!!

The entire course is based of the student interaction and requires basic knowledge of Python and its Libraries.

ThankYou..

Thanks! Overall, it was a good experience learning Python with Coursera. Some quizzes and assignments need to be improved, but overall, it was great. Thanks to Coursera for all the support and financial aid.

Very good course to begin with in the field of Data Science. The analysis of data is very important before we start implementing predictive models on the data, which has been covered very well in the course.

This was a great course and I learnt a lot about data analysis. Instructions were very clear and precise and the course overall was amazing. Recommended Highly who are beginners or intermediate in python.

Its a great introduction a clear explanation about Machine Learning, generation of linear regression models and all the things to do before to the analysis front the data. I'm very excited and gratefullnes.

Even though I know a little about pandas, with this course I was surprised and I was able to learn even more, besides, the examples of statistical tests that are essential in data analysis are very useful.

The course taught me a lot of useful regression techniques in python including multiple linear regression, polynomial transformation, pipelines, ridge regression and gridsearch, an optimization algorithm.

A fast and quick way to get into the data science using Python. The program includes well defined Jupyter notebooks which can be printed out and used a reference. The videos are short and well presented.

Grate course. Really straight forward. I live the design of this course (a lot of quizzes to harden knowledge). I couldn't find any code for box plot during course and I had to make one during assignment.

One of the greatest courses to become familiar with different Python libraries for machine learning, more specifically, the Pandas library, in which we should have the ability to work with "dataframes".

thanks for the powerful content and the knowledge that was shared in the courser i hope that course ill help me in my career and find the first work as data analysis engineer, thanks for the instructor