A Visual Introduction to Algorithms - Free AI-Powered Course

A Visual Introduction to Algorithms

This is an excellent course for an introduction to algorithms designed for early learners who can benefit from and learn algorithms using visual tools.

Beginner

61 Lessons

14h

Certificate of Completion

This is an excellent course for an introduction to algorithms designed for early learners who can benefit from and learn algorithms using visual tools.

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Explanations

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This course includes

11 Playgrounds

18 Challenges

This course includes

11 Playgrounds

18 Challenges

Course Overview

Learn introductory computer science algorithms, including searching, sorting, recursion, and graph theory through a combination of articles, visualizations, quizzes, and coding challenges. Implement Challenges in Java, Python, C++ or Javascript.

TAKEAWAY SKILLS

Python

Programming Language

Algorithms

Searching Algorithms

Course Content

Intro to Algorithms

This chapter introduces algorithms, explaining their importance in problem-solving using a guessing game and route finding examples.

What is an algorithm and why should you care?

A Guessing Game

Route-finding

Binary Search

In this chapter, you will learn about binary search, how to implement it, and its efficiency, with a follow-up quiz.

Binary Search

Implementing Binary Search of an Array

Challenge: Binary Search

Running Time of Binary Search

Quiz: Running time of binary search

Asymptotic Analysis

This chapter introduces asymptotic analysis, focusing on Big-Θ, Big-O, and Big-Ω notations to evaluate algorithm efficiency.

Introduction to Asymptotic notation

Big-θ (Big-Theta) notation

Functions in Asymptotic Notation

Big-O notation

Big-Ω (Big-Omega) notation

Quiz: Asymptotic notation

Selection Sort

In this chapter, you will explore selection sort, including how to swap elements, find minimum values in subarrays, and analyze its performance.

Sorting

Challenge: Implement Swap

Selection Sort Pseudocode

Challenge: Find minimum in Subarray

Challenge: Implement Selection Sort

Analysis of Selection Sort

Insertion Sort

This chapter covers insertion sort, detailing how to insert values into a sorted array, implement the algorithm, and analyze its efficiency.

Insertion Sort

Challenge: Insert a Value Before an Index in Sorted Order

Insertion Sort pseudocode

Challenge: Implement Insertion Sort

Analysis of Insertion Sort

Recursion Algorithms

11 Lessons

In this chapter, you will investigate recursion through problems like computing factorials, checking palindromes, and creating fractals.

Towers of Hanoi

4 Lessons

This chapter focuses on solving the Towers of Hanoi problem, emphasizing recursive solutions and its application in algorithm design.

Merge Sort

6 Lessons

In this chapter, you will learn about merge sort, including its divide-and-conquer approach, merging process, and performance analysis.

Quick Sort

5 Lessons

This chapter covers quicksort, detailing its divide-and-conquer strategy, partitioning method, and efficiency through implementation challenges.

10.

Graphs

3 Lessons

In this chapter, you will explore graphs, including how to represent and store them.

11.

Breadth-first Search

4 Lessons

This chapter introduces breadth-first search (BFS), explaining its algorithm and implementation details, and performance analysis.

12.

License

2 Lessons

The chapter highlights the reasons for adapting a well-known algorithms course and outlines its licensing and collaboration opportunities.

13.

Non-comparison based sorting algorithms

1 Lesson

This lesson works on counting Sort, focusing on its efficiency and data organization method.

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Frequently Asked Questions

What topics does this course cover?

The course covers basic algorithms, including searching, sorting, recursion, and graph theory.

What makes this course unique?

It uses visualizations, quizzes, and coding challenges to teach algorithms interactively.

What programming languages are supported in the coding challenges?

You can implement challenges in Java, Python, C++, or JavaScript.

What learning methods are used in the course?

The course includes articles, visual aids, quizzes, and coding exercises to enhance understanding.

Which type of visualizations are used?

The course uses interactive visualizations to demonstrate how algorithms work step-by-step.

How will this course help me with problem-solving?

The visual approach helps clarify abstract algorithmic concepts, enhancing your problem-solving ability using various methods.