Description
Analysis of temporal and spatial complexity (big-O notation) is a training course on analyzing and estimating the temporal and spatial complexity of algorithms with a big symbol O, published by Udemy Academy. Analyzing the temporal and spatial complexity of algorithms is one of the most valuable and lucrative skills in the field of computer science and programming, which has caught the attention of many engineers and programmers. The topics presented in this course are divided into two areas: theoretical and practical. In the theoretical section with all topics in the field of algorithm analysis such as notations, input cases, amortized complexity analysis, complexity analysis of various information structures, analysis of the amount of resources needed to implement algorithms and .. Get to know them and gain insight.
During the course, the instructor will introduce you to external resources and refer you to books and other teaching tools available if necessary. Practice and testing is one of the most important parts of this training course which can have a great impact on your learning process.
Topics covered in this course:
- Basic Concepts of Algorithm Complexity Analysis
- Familiarity with the symbols of the big O, the big omega and the big theta
- Presentation of different scenarios when receiving data and types of excellent, average and bad scenarios
- Hierarchy of complexities
- Complexity class and its different types such as P and NP
- Different methods for analyzing the temporal and spatial complexity of an algorithm
- Different methods to compare the performance of an algorithm
- Amortized complexity analysis
- Analysis of the complexity of search algorithms
- Analysis of the complexity of sorting algorithms
- Analysis of the complexity of recursive functions
- Analysis of the complexity of the main operators and operators of the data structure
- Common Beginner Problems and Misconceptions
- Familiarity with frequently asked questions and job interview issues
What you will learn in the analysis of time and space complexity (big-O notation)
- Analysis of the temporal and spatial complexity of different algorithms
- Comparison of different algorithms
- Analysis of data search and sorting algorithms
- Different methods for comparing and reviewing algorithms
- Familiarity with complex data structures and large operators
Course specifications
Publisher: Udemy
Instructors: Interior code
French language
Beginner level
Number of lessons: 57
Duration: 7 hours and 35 minutes
Course topics
Analysis of temporal and spatial complexity (big-O notation) Prerequisites
Basic programming knowledge
Pictures
Introductory video to the analysis of temporal and spatial complexity (big-O notation)
Installation guide
After ripping, watch with your favorite player.
english subtitle
Quality: 720p
Download link
File password(s): ngaur.com
Cut
1.55 GB