Hello. Very cool course, designed not for beginners in python. Due to difficulties in translation, I had to additionally search for information on the Internet + take notes in Google documents. Sometimes you get very immersed in the ongoing process and forget about the time. Thanks to course developers.

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.

I always fascinated towards programming languages from university days as it makes the complicated work easier. as having basic cleared about python helps me to sail out through this course. all levels are thoroughly covered with proper scripts which make better understanding even for newcomers also.

Great course with helpful excersise. The only thing that needs to be looked into is peer review for projects. One of the peers rated my project 8 out of 18 and i was asked to re do but because i knew it was correct i just resubmitted without changing anything and 3 peers who reviewed gave me 17/18

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

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.

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!

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.

This course starts with Importing the dataset in Jupyter Notebook, followed by Data Wrangling, Exploratory Data Analysis, Model Development and Model Evaluation, and end with the final assessment applying all the concepts learned.

Thanks to IBM and Coursera for this great learning experience.

the course is too good to be true! it is an elaborate explanation of all the terms with the logic behind it. Seamless experience with the inbuilt code writing lab. I would highly recommend it to all who are at the doorstep of data analysis. This is the first step towards it, and a mighty one!

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

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!

Best wishes!

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).

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

Hi, thank for providing this course. I have a concern about my certificate of data analysis with Python. There is no Coursera logo, and it is different from the other certificates that are related to this course. Please check kindly and let me know how to solve this issue. Thank you.

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.

I have just completed the IBM Data Analyst course "Data Analysis with Python". The course has a lot of practical knowledge with real-life examples and datasets for analysis. Recommended for students of Data Analysis! #python #data #dataanalysis #datasets #IBM #Coursera #HabibManjotha

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!

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.

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!

This course was presented clearly and explained statistical concepts in a way that made them relevant and practical. The assignments were challenging, requiring review of notes and Python techniques made during the lectures, thereby reinforcing the learning outcomes in a good way.

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.

very good and goal oriented cours, no loss of time , covers rapidly subjects that really increase students knowledge on python tools for data analysis. very interesting and useful cover on regression for tolls as well as explaining the statistical concept in a very simple way.

THE RATING IF POSSIBLE TO GIVE 100 THEN I CAN GIVE 100 FOR SURE , BUT OUT OF 5 IT DESERVES 5 WITHOUT ANY DOUBT I CAN SAY THIS COURSE CONTAINS THE ALL BASICS + ENSURES A GOOD UNDERSTANDING OF ALL THE THINGS NEEDED TO DEVELOP THE DATA ANAYSIS SKILLS ALONG WITH PRACTCAL APPROACH .