Algorithms related to searching, sorting and Stacks, Queues, hashmaps, trees, and graphs
Unit 1: Prerequisite Review briefly reviewing key concepts from mathematics (mainly logarithms) and computer science (namely, basic coding and the fundamentals of object-oriented programming).
Unit 2: Asymptotic Analysis analyinge how fast an algorithm is and how much space it uses up. We will discuss how computer scientists formally analyze performance, and use this to develop a number of classes of more performant and less performant algorithms.
Unit 3: Arrays and Linked List Exploring and reviewing the two base data structures for exploring linear information. as
Unit 4: Searching and Sorting Exploring the well-studied problem of searching through and sorting a list. We will delve into some more intuitive but less performant sorting algorithms first, then work our way into more performant algorithms. As part of this unit, we will deep-dive into recursion.
Unit 5: Lists, Stacks and Queues exploring the most common ways to store linear data, including lists, stacks, and queues; we will also explore the operations that are commonly associated to these problems.
Unit 6: General Trees, Binary Trees, Binary Search Trees, Self Balancing Trees, and Heaps exploring our first nonlinear data structure the Tree. During this exploration we will cover, general trees, binary trees, binary search trees, and heaps; we will also explore the operations that are commonly associated to these problems.
Unit 7: Graphs we will explore our second nonlinear data structure the Graph. During this exploration we will cover, directed, undirected, and weighted; we will also explore the operations that are commonly associated to these problems
Unit 8: Maps we will deep-dive into sets and maps, and explore how the concept of hashing makes sets and maps run quickly.