2.1 Elements of Computational Thinking

Computational thinking is a cornerstone of Computer Science, empowering us to approach problems systematically and create efficient, logical solutions. This unit introduces you to the essential principles that form the foundation of problem-solving in programming and algorithm design. You’ll learn how to simplify complex problems through abstraction, break them into manageable parts using decomposition, and apply logical reasoning to develop decision-making processes.

You'll also explore the importance of planning ahead by identifying inputs, outputs, and preconditions, as well as understanding how concurrency and parallelisation allow multiple tasks to be tackled simultaneously. These skills are not only crucial for programming but also have applications in countless other areas, from artificial intelligence and data science to everyday problem-solving.

In this unit, you'll delve into the following subtopics:

1. Thinking Abstractly

2. Thinking Ahead

3. Thinking Procedurally

4. Thinking Logically

5. Thinking Concurrently

Each of these will equip you with tools to analyze, design, and refine solutions to real-world challenges. Let’s begin!