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University of Michigan

Applied Data Science with Python

University of Michigan via Coursera Specialization

Overview

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.

Syllabus

Course 1: Introduction to Data Science in Python
- Offered by University of Michigan. This course will introduce the learner to the basics of the python programming environment, including ... Enroll for free.

Course 2: Applied Plotting, Charting & Data Representation in Python
- Offered by University of Michigan. This course will introduce the learner to information visualization basics, with a focus on reporting and ... Enroll for free.

Course 3: Applied Machine Learning in Python
- Offered by University of Michigan. This course will introduce the learner to applied machine learning, focusing more on the techniques and ... Enroll for free.

Course 4: Applied Text Mining in Python
- Offered by University of Michigan. This course will introduce the learner to text mining and text manipulation basics. The course begins ... Enroll for free.

Course 5: Applied Social Network Analysis in Python
- Offered by University of Michigan. This course will introduce the learner to network analysis through tutorials using the NetworkX library. ... Enroll for free.

Courses

Taught by

Christopher Brooks, Daniel Romero, Kevyn Collins-Thompson and V. G. Vinod Vydiswaran

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