Complexity Calculation

480 hours

lessons

BEGINNER

Course Progress

0 % Complete

1 . Introduction

🔒

Get Started

20 min

2 . Why Analyze Algorithms?

🔒

Introduction

20 min

Analyze Algorithms

20 min

3 . Time Complexity

🔒

Introduction

20 min

Frequency Count Method

20 min

4 . Big O Notation

🔒

Introduction

20 min

Constant Time Complexity

20 min

Linear time complexity

20 min

Quadratic Time Complexity

20 min

Logarithmic Time Complexity

20 min

Big O Complexity Chart

20 min

5 . Asymptotic Notation

🔒

Introduction

20 min

Big Oh (Big O)

20 min

Omega Notation (Ω-notation)

20 min

Theta Notation (θ-notation)

20 min

6 . Calculating Time Complexity

🔒

Linear Search

20 min

Binary Search

20 min

Examples - Time complexity

20 min

7 . Master Theorem

🔒

Introduction

20 min

Master Theorem For Dividing Function

20 min

Master Theorem For Decreasing Function

20 min

8 . Space Complexity

🔒

Calculating Space Complexity

20 min

9 . What's Next?

🔒

What's Next?

20 min

Course Requirements

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About Course

Complexity calculation is the process of analyzing how long an algorithm takes to run and how much memory it uses based on the size of its input. In computer programming, there are multiple ways to solve a problem. Analyzing the complexity of algorithms will help us choose the most efficient solution.

Learn DSA: Complexity Calculation course will help you understand why and how to write code that runs quickly and uses less memory. You will learn to calculate the complexity of algorithms through interactive lessons, examples, quizzes, and challenges.

Course Curriculum

Module 1: Web Development Fundamentals

Module 2: Advanced JavaScript Concepts

Module 3: Building Responsive Layouts

Module 4: Working with APIs

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