Summary Exploring the Foundations of Computer Science: Key Concepts and Principles
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Course
COS1501 - Theoretical Computer Science I
Institution
University Of South Africa (Unisa)
These notes introduce the field of computer science, defining it as the study of computers and computational systems. They cover the basics of computational thinking, which involves breaking down complex problems and designing algorithms to solve them. The notes also provide an overview of algorith...
Introduction to Computer Science:
Computer science is the study of computation, encompassing the theory, design, and applications
of computers and other computational systems.
The process of inventing algorithms to handle big issues by breaking them down into smaller,
more manageable tasks is known as computational thinking.
Problem-solving using Algorithms: Algorithms are a set of detailed instructions or processes.
They serve as the cornerstone for effective problem-solving and are crucial to computer science.
Programming Languages:
Formal languages used to create computer programs are known as programming languages.
Python, Java, and C++ are some examples.
A programming language's syntax is the set of rules that determines its structure and grammar.
Data types, control structures, and variables: Data types specify the types of data that can be
stored in variables, while control structures decide how a program is executed.
Concepts of Object-Oriented Programming (OOP): OOP is a programming paradigm in which
code is organized around objects that have characteristics and methods.
Data Structures:
Collections of elements can be stored and arranged using data structures like queues, stacks,
linked lists, and arrays.
Non-linear data structures that offer effective searching, insertion, and deletion operations
include heaps, binary search trees, and trees.
The Representation of Graphs: Nodes (vertices) and edges make up graphs. Adjacency lists or
adjacency matrices can be used to express them.
Algorithms:
Big O notation is used to evaluate and study the effectiveness of algorithms in terms of their time
and space complexity.
Sorting algorithms include bubble sort, insertion sort, merge sort, and quicksort. They are used to
organize elements in a certain order.
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