Who is this class for: This course is part of the skills-based specialization “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
4.3 stars
Average User Rating 4.3See what learners said
Syllabus

FAQs
How It Works
Coursework
Coursework

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

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Creators
University of Michigan
Pricing
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Ratings and Reviews
Rated 4.3 out of 5 of 31 ratings

This a pretty good introduction to plotting libraries in python. I would have preferred a deeper dive into some of the built-in methods. A little more on visualizations from libraries like seaborn, bokeh, or plotly would have been nice. Overall, great work.

I learned quite a lot about plotting, especially in Python. However, there was a bit too much theory (Cairos principles etc) for my taste.

Good intro to plotting, charting and visualization in Python. Focuses mainly on matplotlib. I feel good about the content that I learned, but also feel like I wanted to learn more in this class. Maybe more coverage of other python charting libraries. More examples of financial type charts -- High/Low/Open/Close etc.

I found the lectures interesting and thorough yet short and to the point.