May 06, 2020
I started this course without any knowledge on Data Analysis with Python, and by the end of the course I was able to understand the basics of Data Analysis, usage of different libraries and functions.
Apr 20, 2019
perfect for beginner level. all the concepts with code and parameter wise have been explained excellently. overall best course in making anyone eager to learn from basics to handle advances with ease.
By Volodymyr C•
Jun 23, 2019
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!
Dec 20, 2018
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
By GURAJALA P•
Aug 07, 2019
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...
By Muhammad Y•
Oct 08, 2018
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.
By Mihailo P•
Apr 12, 2020
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.
By Rohit B•
Mar 16, 2020
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.
By Diderico v E•
Feb 02, 2020
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.
By Stuart S•
Apr 02, 2020
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!
By Dongre O•
May 02, 2020
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.
By MMR R•
May 27, 2019
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.
By David A•
Oct 16, 2019
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.
By Aakanksha P R•
Sep 21, 2020
It is a really well-planned and informative course. The labs provided after every chapter are indeed a lot helpful to understand, recollect and visualize what we learnt during theory lectures. I would recommend this course to all as I found it helpful to improve my Data Analysis & Visualization skills.
By Meenakshi S A•
Nov 20, 2019
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
By Md. R H•
Sep 22, 2019
This course is outstanding valuable for the beginners who wants to build their career as data analysist. I have learned a lots of valuable statistical and progrmming for data analysis. Thanks to all instructor to give us such a opportunity to learn such kind of code and method for data analysis.
By Marta F d O F d N N•
Jun 02, 2020
This was a great introductory course to statistical modeling with Python. I learned a lot of the basic methods to perform linear regression models and to describe statistical variables. The final assignment was slightly challenging, but doable if you follow the labs. All and all a great course!
By Jamiil T A•
Jan 02, 2019
Awesome. A must take course very handy at giving the foundation of data analysis with python and what a nice introduction to linear regression with the library sklearn. For more it looks more like an in-depth course in linear regression. Kudos, the explanations of concepts were well approached.
By Md. A A J•
May 03, 2020
The hands on examples for practicing on IBM cognitive lab, videos and lecturers made are great and helpful. The course contents are clear, precise and lecturer is very knowledgeable.
Joining and getting help from course mates and moderates in discussion forum is Excellent!
Ashfaque A. Joarder
By Gregory J O C•
Jun 27, 2020
I loved this course!
Though, for a beginner like me, it can be kind of confusing to be shown things that are not covered in the course (i.e, plots in which a lot of characteristics have to be set...), this tends to happen in labs.
But for the rest, everything was crystal clear!
By Konstantin D•
Feb 23, 2019
The first "week" was way too simple. I believe things like "what a file path is" should belong to another course. The last 4 "weeks" gave a good picture of where to start with data analysis. The whole course can be completed after 5-10 hours (depends how long you play with the dev tool).
By Sumanta S•
Sep 09, 2020
This course builds your fundamentals of data analysis ,from how to load data to data cleaning, removing missing values, data interpretation, building models, testing them using pipleine to check if model gives proper output , splitting data sets as test set and for model learning. etc
By Surhan Z•
Jun 15, 2019
This course core purpose is to teach the student how to perform analysis in detail. I have taken a lot of courses related to data analysis but no one teaches in detail and gives great examples. I highly recommend this course to all student who wants to learn data analysis with python.
By Vera C•
Jan 16, 2020
This course is actually harder than expected due to the python programming however I felt I truly benefited from it. I have learned and used Python before, but the python code in this course sets a new high bar for me. I'm going to go back and study all the labs in this course again!
By Aman S T•
Apr 19, 2020
This was a good course. It had lot of content you will find data analysis with pandas library along with analysis there is regression machine learning model also and model evaluation section. Overall it was a great experience. Content was nice and I recommend to everyone to enroll.
By Ketan K•
Dec 28, 2018
Really a step up in terms of difficulty compared to "Data Science with Python". Since the final week's content is judged on quiz and not a stand alone assignment, one must revise this course from time to time for the libraries referenced and model analysis approach. Great resource!
By Gajula J•
Jul 16, 2018
This course is very good start for students who are planning to go into machine learning specifically.Students who have no Idea about regression and math find bit hard but little more effort from student side is needed. At the end you will have a zeroth tool for machine learning.