explanation
Time and Space Complexity Analysis (big-O Notation) is a course on analyzing and estimating the time and space complexity of algorithms using big-O notation published by Udemy Academy. Algorithmic time and space complexity analysis is one of the most valuable and money-making skills in computer science and programming, which has captured the attention of many engineers and programmers. The topics presented in this course are divided into two areas: theory and practice. In the theory section, which contains all topics in the field of algorithm analysis, including notation, input cases, amortized complexity analysis, complexity analysis of various information structures, analysis of the amount of resources required to implement algorithms, etc.. Get to know them and get an overview of them.
Throughout the course, instructors will introduce you to external resources and recommend books and other available teaching tools as needed. Practice and testing are one of the most important parts of this course that can have a huge impact on the learning process.
Topics covered in this course:
- Basic concepts of algorithm complexity analysis
- Knowledge of Big O, Big Omega, and Big Theta symbols
- We introduce different scenarios when receiving data and the types of scenarios: good, average, and poor.
- complexity layer
- Complexity classes and various types such as P, NP, etc.
- Various methods for analyzing the temporal and spatial complexity of algorithms
- Different ways to compare algorithm performance
- Amortized Complexity Analysis
- Complexity analysis of search algorithm
- Complexity analysis of sorting algorithm
- Complexity analysis of recursive functions
- Analysis of the main operators and their complexity in data structures
- Common problems and misconceptions of beginners
- We are familiar with frequently asked questions and issues during job interviews.
What to learn from time and space complexity analysis (big-O notation)
- Time and space complexity analysis of various algorithms
- Comparison of various algorithms
- Data search and sorting algorithm analysis
- Different ways to compare and test algorithms
- Knowledge of the complexities of data structures and major operators.
Course specifications
Publisher: Udemy
teacher: internal code
Language:English
Level: Beginner
Number of classes: 57
Duration: 7 hours 35 minutes
course topic
Time and space complexity analysis (big-O notation) prerequisites
basic programming knowledge
movie
Video introducing space-time complexity analysis (big-O notation)
installation manual
After extracting, watch with your favorite players.
English subtitles
Quality: 720p
download link
File password: free download software
size
1.55 GB