Honestly it is one of the best courses I've attended in Data Science. All the ambiguous concepts that I read in the internet and couldn't understand were clear in this course and I didn't have to struggle to get them. The way the course is structured, the visual materials, labs, quizzes and assignments ensure that you leave the the course with good theoretical and technical understanding. Thanks for making it easy to learn Data Science and python! I would definitely recommend this course if you want to have a good start.

Loved the course overall. Truly amazing! Professors did a really great job in making and structuring this course session by session.

A good course to learn know-how of Data Analysis using Python language so as to facilitate analysis and visualization of data to make effective decisions. I thank the professors to make this course interesting and worth it. Only thing is, videos can be made in a better way so as to facilitate people with non programming background. Maybe some basics of programming would help.

Become a Trustworthy Data Analyst

This course provides the knowledge and skills that form the foundation for data analysis. Students learn how to use Python Packages and gain experience creating dataframes and manipulating data sets for computation and visualization. Extensive work on building and evaluating models is included with explanatory lectures and hand-on labs to work with real data. Students' data analysis work will be supported by applying proper of model optimizations learned in the course.

I audited the course. I did not complete the quizzes because my goal was to get a very quick overview of pandas and scikit and pick up on basics. This was at the right level for me and did not go haphazardly. It did not try to convince me that something was simple, hard or not important.

I recommend this as a starting point for most who have little experience with Python but are well-versed in programming otherwise and want to get a look at a little of the ecosystem for ML using Python.

Really good stuff in terms of outlining what is necessary in order to properly analyze the data. One thing to note is the powerpoint slides are off sometimes. Some of the stuff is not spelled correctly in the code.

Another issue is that x and y axis variables will be assigned, but be on the opposite axes (I.E when x = df['price'] but in the scatterplot it's actually the target variable, and thus on the y-axis.

This is an excellent course to begin with analyzing data in python. However, it would have been even more useful and interesting had it contained some more discussions on the topics like logarithmic transformation of features, when to apply it, how to do bi-variate and mutivariate analysis, exercises on topics like manipulation of dataframes using pivot, melt, crosstab etc.

Fantastic introduction to some of main python libraries and functions used in order to do anything related to data analysis, also a good entry point for machine learning, big data and other data science specialisations - highly recommended for anyone comfortable with high level scripting and basic oops concepts - if you don't then best take a basic course in python first...

The course material was excellent , quizzes makes this course more efficient and handy, all the lectures are explained well , the most important part of this course providing notebooks of each week for self practicing and to judge our-self . Discussion forums are provided asking queries, Overall the course was excellent both for beginners and intermediate.

No Doubt COURSERA is always best AND MNC like IBM,Google courses associated with coursera are MIND-BLOWING.

The Instructors are so great at Explanation Part that hardly anyone won't Understand All the Topics

I would love to thank all the INSTRUCTORS who created such a Awesome Content for us.

My Personal Ratings For All the Instructors: 100 / 100

Excellent Course, i've learned a lot, i can analyze any data and give a conclusion from it. It's great course with a very clear explanation. If you are not understanding from the videos you can have a full understanding of the course from the Lab Notebook. The best is giving you a chance to access on IBM Cloud, creating new dynamic projects. Thank you

Initial part of course was easy, but the labs proved more and more useful. As I learned the course, I applied the charting skills directly to work, and was able to use Pandas to combine data from 3 databases, evaluate and report on the data to my company. It is already making a difference in our ability to make better data driven decisions every day.

Great Course! I got a great insight into multiple steps involved in data analysis using python starting from an initial data set to pre-processing it, exploratory analysis, doing multiple operations to create possible models and ways to evaluate the models. I hope to be able to use them to solve some sample data sets and come up with possible models

Did this after Andrew Ng's Machine Learning to learn to do the same things in Python. Great course for people somewhat familiar with Python basics (I used datacamp to get a feel for Python and methods etc. first). Labs were really good for reinforcing knowledge from quizzes and videos. Overall, very nice course - will recommend to others!

This is my first course that i completed, and i am very glad to do this .

thanking you for giving me this opportunity to enrolled this course

i learned a lot of new things from this course this was very fruitful for me.

the slides was nicely represented and the way of teaching was so amazing

i am very very thankful to all the Coursera Team

This course is very use for regression model end to end scratch of evaluation and easily understand the coding theory explanation but ridge regression is somewhat improvement is needed.

Finally, I suggested to this course for learning data analysis with python.

Thanks for wonder full opportunity to learn this course in course-era team...

This course is probably the most concise and well explained course I have ever taken on the subject. Materials are explained very well, and in a concise manner. The only downside is that the assessment for this course is based on quizzes, which are way too easy. Nevertheless, the course contains ungraded labs which are really useful.

This is the most complex course in the IBM Data Specialization Curriculum until now. There is a lot to cover and I would advise the students to go through the notebooks for practice 2 times to make sure to remember everything. One thing that is a bit confusing are functions for creating plots as we did not cover them in details yet.

Awesome course on gaining Python skills for performing structured data analyses. If you are already attending the IBM Data Science certification, this course is a "step up" from the initial courses to bring a lot of things together. I would highly recommend doing it in the recommended order, else the learning curve may be too steep.

Wow! Excellent course that provides a great skills-focused overview on how to do data analysis with Python. The videos are first-rate, high quality and summarize the essential points nicely. The data set is real and it is used throughout the course and that helps understand the different features of data analysis taught by pandas.

Great introduction for using Python for data analysis. I found the segments on using Pandas, scikitlearn, and Matplotlib, particularly useful. Also, the labs' use of Jupyter notebooks, were excellent, because of the ability to introduce new variables or other data, and to see how it affects the outcome. Thank you very much!

This course gave me very good understanding on basic concepts in Data Science and how we can make use of python. I would recommend this course to people who are searching for basics of data science. If you are from programmer then you will be able to correlate software development life cycle and Data Science Development.

It was really helpful for me. Now i can clearly explain what is data. How we can explore data from a big data-set, How we can analyze different type of data-set. I am so much happy with this course. Now i will try to use this technique in my next steps. Special thanks Coursera community for creating this opportunity.

Very useful analytical techniques were learned such as cleaning the data, multiple linear regression, and working with test and training data. This course gave me a good foundation on the approach to analyze large databases. I also feel this will help in learning R because I now know the analytical process.

It was a very interesting and correctly paced course for learning Data Analysis with Python. The course content and the assignments were very helpful in understanding the course well. Will recommend this course to all who want to do a well paced introductory course on Data Analytics using Python