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..

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.

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.

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".

I'm really over-whelmed!...And I mean it. After completing this course one can get a clear insight of data. All topics are clearly explained. All lectures and labs are well structured. Thanks Team IBM!

This course is very good and it covers all the fundamental concepts used by pandas and numpy. It covers the linear regression, ridge search, grid search, polynomial regression and Pipeline construction

It gives a very good introduction on most of the basic statistical methods. It is a bit challenging to absorb it all, but all by all very doable. I enjoyed this one and learned a lot from it! Thank you

Me gustó aprender procesos de análisis de datos, algunos un poco complejos de entender pero se saca el tema. Seria bueno colocar algunas referencias para ir mas en detalle en algunos puntos complejos.

This is totally one of the hardest course I've ever taken on Coursera. It's packed with knowledge I did not know before. Definitely recommended for people who want to learn data analysis with Python.

A compact course. Good one who want to learn within a short period of time. But if one wants to understand the topics well, then he/she should go through the documentation of respective libraries.

Great Introduction to Data Analysis, the concepts going from the basic to deep in data-testing and data-training, as well as several applications linear and polynomial regression to data analyze.