Who is this class for: This course is part of “Applied Data Science with Python“ and is intended for learners who have basic python or programming background, and want to apply statistics, machine learning, information visualization, social network analysis, and text analysis techniques to gain new insight into data. Only minimal statistics background is expected, and the first course contains a refresh of these basic concepts. There are no geographic restrictions. Learners with a formal training in Computer Science but without formal training in data science will still find the skills they acquire in these courses valuable in their studies and careers.


Created by:  University of Michigan

Basic Info
LevelIntermediate
Language
English
How To PassPass all graded assignments to complete the course.
User Ratings
4.5 stars
Average User Rating 4.5See what learners said
Syllabus

FAQs
How It Works
Coursework
Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from Your Peers
Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates
Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

Creators
University of Michigan
The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future.
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Ratings and Reviews
Rated 4.5 out of 5 of 2,143 ratings

The lecturer encourages the student to do a lot of self study and finish very challenging assignments. Very useful course and assignments

It's a very interesting course. very recommended for who wants to acquire Data Science fundamentals using a powerful tool like Python. For who hasn't previous experience with Python it's required an additional time to review examples and docs in the python communities but all assignments are meaningful and the effort has a good payback.

The course is really nice, hands-on all the time. Some questions of the assignments could be improved to avoid ambiguity/subjectivity tough.

a very good introductory course for learning pandas and basic data manipulation with python