FULL MODULE LECTURE NOTES & FLASHCARDS for CO2412 Computational thinking

Contains 15 flashcards

This document provides detailed notes from Lecture 1 of the CO2412 course on Computational Thinking. The lecture introduces the concept of computational thinking, defining it as a universally applicable skill set that goes beyond computer science. The notes cover the four key aspects of computationa...

This document contains detailed notes from Lecture 2 of the CO2412 course on Computational Thinking. The lecture provides an introduction to the Python programming language, focusing on its simplicity, readability, and wide usage in fields such as data science and web development. The notes compare ...

This document contains detailed notes from Lecture 3 of the CO2412 course on Computational Thinking. The lecture focuses on the concept of decomposition, which involves breaking down complex problems into smaller, more manageable parts. This approach is crucial for effective problem-solving in progr...

This document contains comprehensive notes from Lecture 4 of the CO2412 course on Computational Thinking. The lecture focuses on the crucial topic of performance evaluation, highlighting the importance of understanding algorithm efficiency to make informed decisions during algorithm design and optim...

This document contains detailed notes from Lecture 5 of the CO2412 course on Computational Thinking. The lecture provides a comprehensive review of Big O notation, a crucial concept for estimating the time and space efficiency of algorithms, particularly in worst-case scenarios. The notes focus on s...

This document contains comprehensive notes from Lecture 7 of the CO2412 course on Computational Thinking. The lecture explores two important strategies for solving optimization problems: Greedy Algorithms and the Branch and Bound method. It provides an in-depth understanding of how these approaches ...

This document contains comprehensive notes from Lecture 8 of the CO2412 course on Computational Thinking. The lecture focuses on the concept of backtracking, a powerful problem-solving technique that incrementally builds solutions and backtracks when constraints are violated.

This document contains detailed notes from Lecture 9 of the CO2412 course on Computational Thinking. The lecture provides an in-depth exploration of Binary Search Trees (BSTs) and Heaps, two fundamental data structures in computer science.

This document contains comprehensive notes from Lecture 10 of the CO2412 course on Computational Thinking. The lecture introduces the foundational concepts of Graph Theory, a crucial area in computer science for modeling and solving complex problems involving networks of connected objects.

This document contains detailed notes from Lecture 11 of the CO2412 course on Computational Thinking. The lecture focuses on graph traversal, a fundamental concept in computer science that involves visiting and updating each vertex in a graph. The notes cover the two primary methods of graph travers...

This document contains detailed notes from Lecture 12 of the CO2412 course on Computational Thinking. The lecture focuses on pathfinding algorithms, essential tools in computer science for determining the shortest or most efficient path between two points within a graph structure. These algorithms h...

This document contains detailed notes from Lecture 13 of the CO2412 course on Computational Thinking. The lecture introduces the principles of Object-Based Programming (OBP), a component-based approach to software development that focuses on defining and simulating real-world objects through classes...

This document contains comprehensive notes from Lecture 14 of the CO2412 course on Computational Thinking. The lecture introduces the fundamental concepts of probability, a crucial area in mathematics and statistics that measures the likelihood of events occurring. These notes cover the different ty...