Generalisation is a way of quickly solving new problems based on previous problems we have solved. We can take an algorithm that solves some specific problem and adapt it so that it …

In general, computational thinking encompasses the skills one needs to analyze a problem in such a way that one can design a computational solution for the problem, i.e., a solution which …

Recognising patterns – things that are common between problems or programs – is one of the key aspects of computational thinking. Pattern recognition is based on five key steps: …

Examples of Pattern Recognition •We look for patterns when choosing a registrar when we checkout •Drivers look for patterns in traffic to decide whether and when to switch lanes …

• Pattern abstraction is hiding the complexities of one pattern from another. • Pattern generalisation is spotting things that are common between patterns. • We can represent parts …

This is the code repository for Applied Computational Thinking with Python, published by Packt. Design algorithmic solutions for complex and challenging real-world problems

To be able to generalize a solution or algorithm, you need to start developing your ability to recognize patterns. For instance: A sequence of instructions that are repeating multiple times …

Pattern Recognition: Make predictions and models to test. Patten Generalisation and Abstraction: Discover the law, or principles that cause these patterns. Algorithm Design: Develop the …

Understand the core principles of computational thinking, including decomposition and pattern recognition. Develop the ability to break down complex problems into smaller, manageable …

Patterns can help us to solve complex problems more efficiently. Finding the similarities (or patterns) of several problems. Patterns may exist among different problems or within individual …