Programming and Computational Thinking: From Logic to Algorithms

Computational thinking is the foundational problem-solving capability of the 21st century. It is not merely about writing lines of syntax in a programming language; it is the art and science of deconstructing ambiguous, large-scale problems into clear, deterministic, and algorithmically solvable steps.

In this flagship course, you will transition from intuitive thinking to systematic, mathematical computational thinking. You will learn:

• How to decompose real-world complexities into finite states and logical models.
• Pattern recognition, abstraction, and invariant identification.
• Time and space complexity analysis using Big-O, Big-Omega, and Big-Theta notation.
• Fundamental linear and non-linear data structures (Arrays, Linked Lists, Stacks, Queues, Binary Search Trees, and Hash Tables).
• Algorithmic strategies: Divide & Conquer, Dynamic Programming, Greedy approaches, and Graph Traversals (BFS & DFS).
• Hands-on implementation of clean, idiomatic code with robust unit testing.

Who Should Enroll

Whether you are a university student preparing for technical careers, an engineer aiming to ace technical architecture interviews, or a researcher wanting to write high-performance scientific simulations, this curriculum provides the rigorous mathematical and practical foundations you need.