A Quick Introduction to Algorithms

Name: A Quick Introduction to Algorithms
Rating: 4.4 (51 reviews)

Algorithms, Data Structures

Created byAnand Seetharam

Last updated 1/2023

English

What you'll learn

Basics of data structures and algorithms
Different sorting algorithms (Selection Sort, Bubble Sort, Insertion Sort)
Binary search trees and will be able to perform different operations (i.e., search, insertion, deletion)
Graphs (Undirected, Directed, Adjacency Matrix)
Minimum Spanning Trees (Prim's, Kruskals)
Ford Fulkerson's Algorithm
Bipartite Graphs
Minimum Vertex Cover Problem
Two-approximation to minimum vertex cover

Course content

5 sections • 16 lectures • 1h 14m total length

Introduction to Algorithms14:42
In this video, we answer the question - what is an algorithm? This video introduces the concept of algorithms.

Selection Sort6:07
This video explains selection sort in a step-by-step manner using an example and visualization. The pseudocode for selection sort is also provided and the video walks you through the pseudocode.
Bubble Sort3:36
This video explains bubble sort in a step-by-step manner using an example and visualization. The pseudocode for bubble sort is also provided and the video walks you through the pseudocode.
Insertion Sort3:02
This video explains insertion sort in a step-by-step manner using an example and visualization. The pseudocode for insertion sort is also provided and the video walks you through the pseudocode.

Binary Search Trees: Introduction1:18
This video introduces the concept of binary search trees and outlines its key properties.
Binary Search Trees: Insertion0:43
This video describes how to insert a node into a binary trees using an illustrative example.
Binary Search Trees: Deletion3:22
This video describes the process of deleting nodes from a binary search tree using an illustrative example. The video describes all the three cases that arise when removing nodes from a binary search tree.
Binary Search Trees: Search1:04
This video describes how to search for a particular key value (or content) in a binary search tree using an illustrative example.

Introduction to Graphs10:59
In this video, I provide an overview of graphs and discuss how to represent graphs using adjacency lists and adjacency matrices.
Minimum Spanning Trees: An Introduction5:03
In this video, we provide an overview of minimum spanning trees in a weighted unidirectional graph.
Prim's Algorithm4:13
This video explains Prim's Algorithm for finding the minimum spanning tree in a step-by-step manner using an example and visualization. The pseudocode for Prim's Algorithm is also provided and the video walks you through the pseudocode.
Kruskal's Algorithm3:07
In this video, we study Kruskal's algorithm to find the minimum spanning tree in a graph. The approach covered in this video is a very simple one and is useful to understand more efficient implementations of Kruskal's algorithm.

Bipartite Graphs and Maximum Matching5:37
In this video, we describe bipartite graphs and maximum matching in bipartite graphs. The video describes how to reduce bipartite matching to the maximum network flow problem.
Ford Fulkerson Maximum Flow Algorithm5:42
In this video, we describe Ford-Fulkerson's algorithm for solving the maximum network flow problem using visualization and a simple example. The video provides pseudocode for the algorithm and explains the algorithm using a step-by-step approach.
Minimum Vertex Cover4:31
In this video, we study the minimum vertex cover problem of a graph. Finding the minimum vertex cover is an NP-complete problem. The video explains the brute force algorithm to find the minimum vertex cover in a graph using an illustrative example.
I misspoke a couple of times in this video - When I say "it covers/does not cover all the vertices" , I actually meant to say "it covers/does not cover all the edges".
Two Approximation Algorithm for Minimum Vertex Cover1:44
This video explains the two approximation algorithm for the minimum vertex cover of a graph in a step-by-step manner using an example and visualization. The pseudocode for the 2-approximation algorithm is also provided and the video walks you through the pseudocode.

Requirements

No programming experience needed.

Description

Data Structures and Algorithms is one of the core topics in computer science. Being able to design and analyze algorithms is one of the most important skills required by computer science students and software professionals. All major software companies (e.g., Google, Meta, Microsoft) ask a variety of questions related to algorithms in their interviews.

This short course is designed to provide a quick overview of a variety of different algorithms. This course is ideal for individuals who seek a quick yet comprehensive refresher to data structures and algorithms (e.g., while preparing for an exam or job interviews). This course is also well-suited for individuals who are enthusiastic about computer science and want to obtain a high-level understanding of various algorithms.

Upon successful completion of this course, students will be able to understand, explain and apply key algorithmic concepts related to sorting algorithms (selection sort, bubble sort, and insertion sort). The course will also introduce Binary Search Trees and the various actions supported by them (i.e., insertion, deletion and search). Students will also be introduced to graph and graph algorithms. Specifically, we will cover minimum spanning tree algorithms such as Prim's Algorithm and Kruskal's Algorithm. The course also includes advanced topics such as bipartite graphs, Ford Fulkerson's Algorithm and minimum vertex cover.

Who this course is for:

Beginners
Individuals who need a refreshers to Algorithms
Candidates preparing for interviews in time crunch

A Quick Introduction to Algorithms

What you'll learn

Explore related topics

Course content

Introduction1 lecture • 15min

Sorting Algorithms3 lectures • 13min

Binary Search Trees4 lectures • 6min

Graphs4 lectures • 23min

Advanced Graph Algorithms4 lectures • 18min

Requirements

Description

Who this course is for: