Chapter 1: Understanding Computational Thinking

Computational thinking is a structured approach to problem-solving that incorporates strategies and concepts from computer science. This mindset transcends mere programming or computer use; it is a versatile toolkit that can be applied across numerous disciplines and everyday challenges.

Photo by Trevor Vannoy on Unsplash

The application of computational thinking spans various domains, including mathematics, science, business, and social sciences. It empowers individuals to systematically dissect problems and devise effective solutions, making it an essential skill in today’s technology-centric environment.

MIT offers a free-to-audit course titled "Computational Thinking for Modeling and Simulation." Who doesn’t appreciate free educational resources?

Course Details:

• Duration: 9 weeks
• Level: Intermediate
• Prerequisites: Algebra, Calculus

Syllabus Overview:

• What is Computational Thinking? (representation, discretization, error, decomposition, verification)
• Interpolation (creating simple models for complex functions)
• Integration (numerical quadrature techniques)
• Randomness (generating and utilizing pseudorandom variables)
• Differentiation (calculating numerical derivatives)
• Solving equations (Gaussian elimination for linear systems, Newton-Raphson for non-linear systems)

While the course is labeled as intermediate, the syllabus suggests that beginners may also benefit from it. I strongly encourage anyone interested in natural sciences such as physics or chemistry to consider enrolling.

The course is instructed by Daniel Frey, a professor in the Mechanical Engineering Department at MIT, and Ali Talebinejad, a lecturer in the same department.

If you share my enthusiasm for free resources, be sure to follow me and subscribe to my newsletter, where I’ll share more opportunities related to scholarships, fellowships, and data science topics. If you enjoyed this article, please clap and share it. Until next time!

You can support my work on Kofi.

Explore More Free Courses and Scholarships

Chapter 2: Video Insights on Computational Thinking

This section features insightful videos that delve deeper into computational thinking and its applications.

The first video, "Linear Models and Simulations | MIT Computational Thinking Spring 2021 | Lecture 15," provides an in-depth exploration of linear models and their role in simulations.

The second video, "1. Introduction, Optimization Problems (MIT 6.0002 Intro to Computational Thinking and Data Science)," presents foundational concepts in optimization and computational thinking.