A Visual Introduction to Algorithms

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.

AI-POWERED

Explanations

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Explanations

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

1.

Intro to Algorithms

This chapter introduces algorithms, explaining their importance in problem-solving using a guessing game and route finding examples.
2.

Binary Search

In this chapter, you will learn about binary search, how to implement it, and its efficiency, with a follow-up quiz.
3.

Asymptotic Analysis

This chapter introduces asymptotic analysis, focusing on Big-Θ, Big-O, and Big-Ω notations to evaluate algorithm efficiency.
4.

Selection Sort

In this chapter, you will explore selection sort, including how to swap elements, find minimum values in subarrays, and analyze its performance.
5.

Insertion Sort

This chapter covers insertion sort, detailing how to insert values into a sorted array, implement the algorithm, and analyze its efficiency.
7.

Towers of Hanoi

4 Lessons

This chapter focuses on solving the Towers of Hanoi problem, emphasizing recursive solutions and its application in algorithm design.
8.

Merge Sort

6 Lessons

In this chapter, you will learn about merge sort, including its divide-and-conquer approach, merging process, and performance analysis.
9.

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?

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