Applied Data Science with Python
Description
The 5 courses in this University of Michigan specialization introduce learners to data science through the python programming language. This skills-based specialization is intended for learners who have a basic python or programming background, and want to apply statistical, machine learning, information visualization, text analysis, and social network analysis techniques through popular python toolkits such as pandas, matplotlib, scikit-learn, nltk, and networkx to gain insight into their data.
Introduction to Data Science in Python (course 1), Applied Plotting, Charting & Data Representation in Python (course 2), and Applied Machine Learning in Python (course 3) should be taken in order and prior to any other course in the specialization. After completing those, courses 4 and 5 can be taken in any order. All 5 are required to earn a certificate.
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Subjects
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Language
English
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Duration
20 weeks
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Status
Available
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U-M Credit Eligible
No
Instructors
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Christopher Brooks
Associate Professor of Information
School of Information
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Kevyn Collins-Thompson
Associate Professor
School of Information
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Daniel Romero
Assistant Professor
School of Information
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V.G. Vinod Vydiswaran
Assistant Professor
School of Information
Courses (5)
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Introduction to Data Science in Python
|4 weeks
This course will introduce the learner to the basics of the python programming environment, including … -
Applied Plotting, Charting & Data Representation in Python
|4 weeks
This course will introduce the learner to information visualization basics, with a focus on reporting … -
Applied Machine Learning in Python
|4 weeks
This course will introduce the learner to applied machine learning, focusing more on the techniques … -
Applied Text Mining in Python
|4 weeks
This course will introduce the learner to text mining and text manipulation basics. The course … -
Applied Social Network Analysis in Python
|4 weeks
This course will introduce the learner to network analysis through tutorials using the NetworkX library. …
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