CF

Foundations of Algorithms Masterclass

5h 34m 12s
English
Paid

Foundations of Algorithms Masterclass is a 65-lesson 5 hours 34 minutes self-paced course by The Net Ninja. Masterclass on Algorithm Basics — is your reliable starting point for developing structural thinking , preparing for technical interviews, and confidently handling tasks of any complexity.

Course facts

Lessons
65
Duration
5 hours 34 minutes
Level
All levels
Language
English
Updated
Instructor
The Net Ninja
Price
Premium

Masterclass on Algorithm Basics — is your reliable starting point for developing structural thinking, preparing for technical interviews, and confidently handling tasks of any complexity. The course explains complex topics in simple language and shows how to apply algorithms in practice.

What to Expect in This Masterclass

The course combines theory, practice, and analysis of typical mistakes so that you can not only understand algorithms but also confidently apply them in real projects.

  • Step-by-step explanation of key concepts
  • Discussion of practical examples and problems
  • Visual demonstrations of algorithms in code
  • Focus on efficiency and optimization

Main Topics of the Course

1. Basic Algorithm Concepts

Understanding what algorithms are, where they are applied, and why they are important in modern development.

  • Definition and properties of algorithms
  • Complexity analysis: Big O, time, and memory
  • Comparison of different approaches to problem-solving

2. Recursion and Decomposition Strategies

Exploration of recursive thinking and typical patterns encountered in algorithmic problems.

3. Sorting and Searching Algorithms

From classical methods to optimized variants — with detailed visualization and examples.

4. Dynamic Programming

Building efficient solutions by breaking tasks into subproblems, memoization, and tabulation.

Who Will Benefit from This Masterclass

  • Beginner developers looking to strengthen their foundation
  • Those preparing for technical interviews in large IT companies
  • Students and self-taught individuals learning algorithms for the first time
  • Developers seeking to systematize their knowledge

What You Will Gain in the End

Upon completing the course, you will be able to:

  • Confidently assess the efficiency of algorithms
  • Consciously choose optimal solutions for tasks
  • Understand how to structure and optimize code
  • Think like an engineer capable of solving complex algorithmic problems

Additional

https://github.com/iamshaunjp/foundations-of-algorithms-masterclass

Who teaches Foundations of Algorithms Masterclass? The Net Ninja

The Net Ninja thumbnail

The Net Ninja is the YouTube channel and paid-course brand of Shaun Pelling, a UK-based developer behind one of the largest independent web-development tutorial channels online. The channel has been publishing daily-or-near-daily web-development content for nearly a decade and has anchored a generation of self-taught developers' first exposure to JavaScript, React, Vue, Node.js, and the modern front-end ecosystem.

His CourseFlix listing carries four Net Ninja courses: TypeScript Masterclass, Flutter Masterclass (covering cross-platform mobile development), Nuxt 3 With Pinia, and Redis Stack Tutorial. The teaching style is calm, patient, and accessible to absolute beginners — the channel's signature for nearly a decade.

Material is paid for the longer courses; much of Shaun's introductory content is also free on YouTube. Courses are aimed primarily at self-taught developers building real web and mobile proficiency.

What lessons are included in Foundations of Algorithms Masterclass?

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#1: 1 - Introduction
All Course Lessons (65)
#Lesson TitleDurationAccess
1
1 - Introduction Demo
03:21
2
2 - What is an Algorithm?
10:36
3
3 - Using Pseudocode to Help Solve Problems
06:28
4
4 - VS Code Setup & Course Files
02:38
5
5 - Introduction to Time Complexity
06:09
6
6 - Introduction to Big O Notation
03:42
7
7 - Constant Time Complexity
05:52
8
8 - Linear Time Complexity
04:01
9
9 - Quadratic Time
06:42
10
10 - CHALLENGE - Time Complexity Quiz
01:39
11
11 - SOLUTION - Time Complexity Quiz
07:03
12
12 - Logarithmic Time
09:59
13
13 - CHALLENGE - Only Positive Numbers
01:47
14
14 - SOLUTION - Only Positive Numbers
04:13
15
15 - CHALLENGE - Staircase Problem
05:05
16
16 - SOLUTION - Staircase Problem
12:02
17
17 - Arrays & Objects
04:55
18
18 - Space Complexity
03:28
19
19 - Introduction to Recursion
05:21
20
20 - ASIDE - The Call Stack
07:06
21
21 - Recursion Example
08:25
22
22 - CHALLENGE - Recursive Fibonacci
02:06
23
23 - SOLUTION - Recursive Fibonacci
05:48
24
24 - Time Complexity of Recursive Algorithms
03:14
25
25 - Introduction to Memoization
02:14
26
26 - Adding Memoization to a Recursive Algorithm
08:48
27
27 - CHALLENGE - Adding Memoization to the Staircase Problem
00:30
28
28 - SOLUTION - Adding Memoization to the Staircase Problem
02:13
29
29 - Space Complexity with Recursion
02:16
30
31 - Linear Search Theory
01:50
31
30 - Introduction to Search Algorithms
01:23
32
32 - Linear Search Implementation
05:32
33
33 - Binary Search Theory
02:45
34
34 - Binary Search Implementation
09:20
35
35 - CHALLENGE - Recursive Binary Search
02:18
36
36 - SOLUTION - Recursive Binary Search
04:22
37
37 - Introduction to Sorting
01:39
38
38 - Bubble Sort Theory
04:09
39
39 - Bubble Sort Implementation
07:24
40
40 - CHALLENGE - Optimizing Bubble Sort
03:01
41
41 - SOLUTION - Optimizing Bubble Sort
04:02
42
42 - Selection Sort Theory
02:50
43
43 - CHALLENGE - Selection Sort Implementation
02:15
44
44 - SOLUTION - Selection Sort Implementation
08:41
45
45 - Merge Sort Theory
04:13
46
46 - Merging Two Arrays Together
11:48
47
47 - CHALLENGE - Merge Sort Implementation
02:33
48
48 - SOLUTION - Merge Sort Implementation
09:53
49
49 - Divide & Conquer
08:56
50
50 - Dynamic Programming
12:16
51
51 - Frequency Counting
08:28
52
52 - Multiple Pointers
05:36
53
53 - Sliding Window
09:51
54
54 - Challenges Introduction
01:44
55
55 - CHALLENGE - Greatest Common Divisor
05:03
56
56 - SOLUTION - Greatest Common Divisor
06:07
57
57 - CHALLENGE - Cartesian Product
01:39
58
58 - SOLUTION - Cartesian Product
03:49
59
59 - CHALLENGE - Palindromes
01:41
60
60 - SOLUTION - Palindromes
03:24
61
61 - CHALLENGE - Longest Substring
02:39
62
62 - SOLUTION - Longest Substring
08:28
63
63 - CHALLENGE - Minimum Coin Change Problem
04:33
64
64 - SOLUTION - Minimum Coin Change Problem
11:37
65
Wrap Up
00:42
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Frequently asked questions

What are the prerequisites for enrolling in this course?
The course is designed for beginner developers, so no extensive prior knowledge is required. However, a basic understanding of programming concepts and familiarity with a programming environment such as VS Code will be helpful. The course includes a lesson on setting up VS Code and accessing course files, which can assist those new to using development tools.
What can I expect to build or achieve by the end of the course?
By the end of the course, you will have a solid understanding of algorithmic concepts such as recursion, sorting, and dynamic programming. You will work on practical challenges like the Staircase Problem and implementing sorting algorithms such as Bubble Sort and Merge Sort. These exercises aim to enhance your problem-solving skills and prepare you for technical interviews.
Who is the target audience for this course?
This course is ideal for beginner developers looking to build a strong foundation in algorithms. It is also beneficial for those preparing for technical interviews at large IT companies or students who want to deepen their understanding of algorithmic thinking and problem-solving strategies.
How does the depth of this course compare to similar courses?
The course offers a balanced mix of theory, practical examples, and problem-solving challenges. It covers foundational topics like time complexity and Big O notation in detail, alongside practical challenges that encourage applying learned concepts. This course is structured to provide a comprehensive understanding suitable for beginners, with a focus on efficient problem-solving techniques.
What specific tools or platforms will I learn to use in this course?
The course involves using VS Code for coding exercises, as covered in the lesson on VS Code Setup & Course Files. Additionally, you will learn to use pseudocode to help solve problems. These tools are integral to understanding and implementing the algorithmic concepts taught throughout the course.
What topics are not covered in this course?
The course focuses on foundational algorithmic concepts and does not cover advanced data structures or algorithms beyond dynamic programming, sorting, and searching. Topics like graph algorithms or machine learning algorithms are not included. The course is designed to establish a strong base for further exploration into more complex areas.
What is the expected time commitment for completing this course?
The course comprises 65 lessons, with a mix of theoretical explanations and practical challenges. While the runtime is not specified, learners should expect to spend additional time on exercises and challenges. The time commitment can vary based on individual pace, but regular study over several weeks is recommended to absorb and practice the material thoroughly.