Applied Data Science with Python Specialization

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.

Advanced 0(0 Ratings) 0 Students enrolled English
Created by Thi Nguyen Van
Last updated Thu, 15-Aug-2024
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Course overview

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.

Curriculum for this course
5 Lessons 00:00:00 Hours
Introduction to Data Science in Python
3 Lessons 00:00:00 Hours
  • Understand techniques such as lambdas and manipulating csv files
    .
  • Describe common Python functionality and features used for data science
    .
  • Query DataFrame structures for cleaning and processing
    .
Applied Plotting, Charting & Data Representation in Python
2 Lessons 00:00:00 Hours
  • Describe what makes a good or bad visualization
    .
  • Understand best practices for creating basic charts
    .
Applied Machine Learning in Python
0 Lessons 00:00:00 Hours
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About instructor

Thi Nguyen Van

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