This course will introduce the core data structures of the Python programming language. We will move past the basics of procedural programming and explore how we can use the Python built-in data structures such as lists, dictionaries, and tuples to perform increasingly complex data analysis. This course will cover Chapters 6-10 of the textbook “Python for Everybody”. This course covers Python 3.
About this Course
Learner Career Outcomes
Learner Career Outcomes
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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TOP REVIEWS FROM PYTHON DATA STRUCTURES
Excellent explanation. Professor Charles kept the course from being monotonous. Learnt in depth about reading from file, sorting dictionaries and appending lists. Looking forward to learn more courses
assignment 9.4 auto grader not working . LTI unable to launch.\n\nerror message: This tool should be launched from a learning system using LTI.\n\ni am using chrome on mac book air 2 and python 3.6
Loved this course as it teaches you to get started with python and Dr.Chuck has made this course very much engaging and interesting. I would suggest to take this course in the order of specialization.
Great course for pyhton. Loved this course and enjoyed it. Thanks to Dr.Chuck. If anyone who want to take a course which is well explained and fun for python learning, then Hey!!! this is your course.
About the Python for Everybody Specialization
This Specialization builds on the success of the Python for Everybody course and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. In the Capstone Project, you’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization.
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