Time and space complexity analysis (big-O notation)

Learn how to analyze the time complexity and the space complexity of an algorithm by using the big O notation

4.38 (230 reviews)

Udemy

platform

English

language

Engineering

Why take this course?

🎓 Course Title: Time and Space Complexity Analysis (Big-O Notation) 🚀

Headline: 🌟 Dive into Mastering Algorithm Efficiency with Big-O Notation! 🌟

Course Description:

📚 What You'll Learn:

Complexity Analysis Basics
- Understanding the fundamental concepts of complexity analysis
Big-O, Big-Omega, and Big-Theta Notations
- Mastering the three main notations for understanding algorithm efficiency
Best, Average, and Worst Case Complexities
- Analyzing different scenarios of an algorithm's performance
Complexities Hierarchy
- Exploring the hierarchy and implications within algorithm complexities
Complexity Classes (P vs NP Problem)
- Diving into the world of complexity classes and their significance in computational theory
How to Analyze Time and Space Complexity of an Algorithm
- Practical skills for evaluating efficiency from various perspectives
How to Compare Algorithms Efficiency
- Learning techniques for assessing and comparing algorithms
Amortized Complexity Analysis
- Understanding amortization and its role in complexity analysis
Complexity Analysis of Searching Algorithms
- Analyzing the efficiency of search operations and data retrieval mechanisms
Complexity Analysis of Sorting Algorithms
- Learning how to assess sorting algorithms for time and space efficiency
Complexity Analysis of Recursive Functions
- Breaking down recursive problems into simpler, understandable parts
Complexity Analysis of Data Structures Main Operations
- Investigating the efficiency of operations on common data structures
Common Mistakes and Misconceptions
- Identifying and avoiding frequent errors in complexity analysis
Complexity Analysis of Some Popular Interview Coding Problems
- Applying your skills to solve real-world interview problems with confidence