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Python Programming: Learn Computer Science Fundamentals
Master computer science fundamentals and Python programming in this comprehensive MIT course designed for beginners to solve real-world analytical problems.
Master computer science fundamentals and Python programming in this comprehensive MIT course designed for beginners to solve real-world analytical problems.
This foundational course introduces computer science and programming using Python 3.5, focusing on computational thinking and problem-solving skills. Students learn to write programs for practical problem-solving, covering core concepts from basic algorithms to data structures. The course emphasizes breadth over depth, providing a comprehensive introduction to computer science concepts while developing practical programming skills. It serves both as a standalone course for general computational literacy and as a foundation for more advanced computer science studies. The curriculum combines theoretical concepts with hands-on programming practice, featuring interactive lectures, coding exercises, and challenging problem sets.
4.6
(296 ratings)
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Instructors:
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What you'll learn
Develop a foundational understanding of computation and programming
Master basic Python programming language syntax and concepts
Implement and analyze simple algorithms for problem-solving
Practice effective testing and debugging techniques
Understand basic algorithmic complexity concepts
Work with fundamental data structures in Python
Skills you'll gain
This course includes:
Live video
Graded assignments, exams
Access on Mobile, Tablet, Desktop
Limited Access access
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Module Description
This comprehensive introduction to computer science uses Python 3.5 to teach fundamental programming concepts and problem-solving skills. The course covers computational thinking, basic algorithms, data structures, testing, and debugging. Students learn through a combination of video lectures, programming exercises, and challenging problem sets. The course emphasizes practical application while providing a broad foundation in computer science principles. It's designed to help students develop the ability to write programs to solve real-world analytical problems.
Fee Structure
Instructors
3 Courses
Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT
John Guttag is the Dugald C. Jackson Professor of Computer Science and Electrical Engineering at MIT, where he leads the Data Driven Medical Research Group within the Computer Science and Artificial Intelligence Laboratory (CSAIL). His research focuses on applying advanced computational techniques to medicine, with current projects aimed at predicting adverse medical events, assessing patient-specific responses to therapies, developing non-invasive monitoring tools, and enhancing telemedicine capabilities.
4 Courses
Senior Lecturer in Computer Science and Electrical Engineering at MIT
Ana Bell is a Senior Lecturer in the Department of Electrical Engineering and Computer Science (EECS) at the Massachusetts Institute of Technology (MIT), where she has been teaching introductory computer science since 2013. She holds a Bachelor of Applied Science from the University of British Columbia, as well as both an MA and PhD from Princeton University, where her research focused on computational biology.
Testimonials
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4.6 course rating
296 ratings
Frequently asked questions
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