Principles of Computing (Part 1)
This course is part of Fundamentals of Computing.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Fundamentals of Computing Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Master Python programming standards and testing
Apply probability concepts to computational problems
Implement combinatorics in practical applications
Develop debugging and testing strategies
Create efficient algorithmic solutions
Build strategy-based game projects
Skills you'll gain
This course includes:
5.4 Hours PreRecorded video
5 assignments
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course combines programming skills with mathematical problem-solving principles. Students learn essential computing concepts through Python programming, focusing on coding standards, testing, and practical applications. The curriculum covers probability, combinatorics, and counting, with weekly mini-projects involving strategy-based games. The course emphasizes both theoretical understanding and hands-on implementation, preparing students for advanced computational problem-solving.
Required Python knowledge, coding standards, and machine grading
Module 1 · 5 Hours to complete
Testing, plotting, and grids
Module 2 · 2 Hours to complete
Probability, randomness, and objects/references
Module 3 · 3 Hours to complete
Combinatorics, generators, and debugging
Module 4 · 3 Hours to complete
Counting, growth of functions, higher-order functions
Module 5 · 3 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Fundamentals of Computing
Instructors
Professor and Researcher
Scott Rixner is a Professor of Computer Science at Rice University, where his research primarily focuses on virtualization, operating systems, and computer architecture. He is particularly interested in memory systems and networking, exploring the intersection of hardware and software to enhance system performance. Rixner has developed Python interpreters for various platforms, including embedded systems and web browsers, and holds 11 patents related to his work, which has been integrated into several open-source projects.In addition to his research, Rixner plays a significant role in curriculum development at Rice University, having chaired committees for both the Department of Computer Science and the School of Engineering. He is also involved in leading the MCS@Rice and MDS@Rice online degree programs. Rixner earned his Ph.D. in Electrical Engineering from MIT in 2001, following a Master’s and Bachelor’s degree in Computer Science and Electrical Engineering from the same institution in 1995.
Innovator in Computer Graphics and Game Design
Joe Warren is a Professor in the Department of Computer Science at Rice University, where he specializes in computer graphics and geometric modeling. He has made significant contributions to the field, authoring the book Subdivision Methods for Geometric Design and publishing extensively on various topics within computer graphics. Warren has a strong passion for computer gaming, both as a player and an educator; he has taught courses on game creation and design for over a decade, collaborating with industry professionals in Houston. An alumnus of Rice University, he completed his undergraduate studies there before earning his Ph.D. from Cornell University in 1986. Since then, he has been a dedicated faculty member at Rice, serving as the Chair of the Department from 2008 to 2013.
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