Principles of Computing: Algorithmic Thinking in Python

To write truly efficient software, you need to understand the core mathematical and logical principles that govern how computers solve problems. This course bridges the gap between basic coding syntax and genuine computer science, helping you think like a systems architect. You will transition from writing simple scripts to designing structured, optimized computational solutions. Through clear text-based explanations and practical coding exercises, you will learn how to analyze problem complexity, structure data logically, and write clean, modern Python code that scales. What you'll learn: - Understand core computer science concepts including recursion, search algorithms, and basic data structures. - Analyze the efficiency of your code using Big O notation and algorithmic complexity principles. - Apply mathematical concepts like probability and combinatorics to solve practical computational challenges. - Write robust, readable code using modern Python features such as type hints and basic testing with pytest. - Implement classic sorting and searching algorithms from first principles. - Practice structured problem-solving by breaking complex computational problems into manageable, modular components. The course begins with foundational concepts of algorithmic complexity and mathematical reasoning before guiding you through the step-by-step written implementation of classic data structures and algorithms. This course is designed for self-taught programmers, students, and aspiring software developers who already know basic Python syntax and want to build a rock-solid computer science foundation. No advanced mathematics background is required. Start thinking like a computer scientist and elevate your programming skills today.