Computational Thinking (CO2412)

This document contains detailed notes from Lecture 20 of the CO2412 course on Computational Thinking, focusing on exam revision topics including propositional logic and statistical measures. The lecture covers essential concepts such as the validity of arguments, logical equivalence, and key measures of central tendency and variation, providing a strong foundation for the upcoming exam.

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 programming, as it leads to better organization, modularity, and easier debugging.

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 Python with C++, highlighting the differences in execution speed, typing, and learning curve.

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 traversal: Breadth-First Search (BFS) and Depth-First Search (DFS).

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 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 simplifying complexity estimations by highlighting the fastest-growing terms and discarding less significant details.

This document contains detailed notes from Lecture 17 of the CO2412 course on Computational Thinking, focusing on the fundamentals of propositional logic. The lecture provides a thorough introduction to propositional logic, which is used to assess the validity of arguments by applying logical rules to determine whether conclusions drawn from premises are sound.

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 types of probability, including classical, frequentist, and subjective probability, providing clear definitions and examples for each.