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Mastering Time & Space Complexity Analysis - OneDDL - 08-09-2024
![[Image: 8329ebc83400c5c96f4d3dca397a4a98.jpeg]](https://i123.fastpic.org/big/2024/0808/98/8329ebc83400c5c96f4d3dca397a4a98.jpeg)
Free Download Mastering Time & Space Complexity Analysis
Published 7/2024
Created by Sanket Singh
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 35 Lectures ( 4h 18m ) | Size: 2.8 GB
Big O Notation, Time Complexity Classes, Space Complexity, Best, Worst, and Average Cases
What you'll learn:
Understand Big O Notation: Grasp and apply Big O notation to analyze algorithm efficiency, covering both time and space complexity.
Understand Big O Notation: Grasp and apply Big O notation to analyze algorithm efficiency, covering both time and space complexity.
Optimize Code for Efficiency: Learn techniques to optimize code, reducing time and space complexity, and improving application performance.
Apply Complexity Analysis: Apply time and space complexity analysis to real-world scenarios, solving practical problems and understanding algorithm trade-offs.
Differentiate Complexity Classes: Distinguish between different complexity classes (constant, logarithmic, linear, quadratic, etc.) and understand their implica
Utilize Data Structures Efficiently: Learn how to choose and utilize appropriate data structures to optimize algorithms for better time and space efficiency.
Requirements:
Very basic of any programming language is enough
Description:
In this comprehensive online course, you will learn everything you need to know about analyzing the efficiency of algorithms, including time and space complexity. The course covers both the basics and advanced concepts of time and space complexity analysis, starting from the fundamentals and building up to more complex techniques.Throughout the course, you will learn how to analyze algorithms and estimate their time and space complexity using various tools and techniques, such as big O notation, asymptotic analysis, worst-case and average-case analysis, and more. You will also learn how to evaluate the trade-offs between different algorithms based on their time and space complexity and choose the most efficient one for a particular problem.In addition to theoretical concepts, the course also includes practical examples and exercises to help you develop hands-on skills in time and space complexity analysis. You will have the opportunity to work with real-world problems and datasets and apply your newly acquired knowledge to solve them.Whether you are a beginner or an experienced programmer, this course will provide you with a solid foundation in time and space complexity analysis, an essential skill for anyone working in the field of computer science, data science, or artificial intelligence. By the end of the course, you will have the confidence and skills to analyze any algorithm and make informed decisions about the best approach to solve a particular problem.
Who this course is for:
Computer science students seeking to understand algorithm efficiency.
Software developers aiming to optimize their code for better performance.
Coding enthusiasts preparing for technical interviews or competitive programming.
Beginners looking for foundational knowledge in time and space complexity.
Experienced programmers wanting to refine their skills in algorithm analysis.
Learners with basic programming knowledge aiming to deepen their understanding of optimization techniques.
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