Udemy- Analysis of Algorithms
MP4 | Video: h264, 1280x720 | Audio: AAC, 48 KHz, 2 Ch
Genre: eLearning | Language: English | Duration: 34 lectures (3 hour, 46 mins) | Size: 1.69 GB
Be an EXPERT in analysing Algorithms & boost your Software career
What you'll learn
This course will lay a solid foundation on which you can develop and analyze your algorithms.
You will learn to measure the performance of your algorithm in terms of the standard notations used in the industry.
Taking this course will help you to ace your upcoming coding interviews.
Requirements
Basic knowledge of Mathematics is required.
Description
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Analysis of Algorithms course is well-structured into a curriculum of 20+ video lectures, a wide variety of practice examples, quizzes & practice worksheets to test your understanding.
The curriculum focuses on the following topics:
Basics of Algorithms: All you need to know about algorithms before learning to analyse them.
Time and Space Complexity: These are the major factors on which the efficiency of your algorithm depends.
Types of Analysis: Different situations while analysing an algorithm which are Worst Case, Average Case & the Best Case.
Asymptotic Notations: The industry standard adopted worldwide for notifying algorithms majorly Big-O Notation, Omega Notation & the Theta Notation.
Important Algorithmic paradigms such as Recursion, Divide & Conquer which you will come across heavily while solving a coding problem whether in your academic curriculum or in your Interview.
Recurrence Relations and all types of recurrence relations you will come across in all recursive problems.
Solving Recurrence Relations: using Substitution, Recursive Tree & Master theorem method.
Taking this course will also help you in your upcoming coding interview.
You can apply algorithmic analysis process on your Java, Python, Javascript, C, C++ or any other language code.
Who this course is for:
If you are studying/undertaking Computer Science in Undergrad school.
If you are preparing for a Coding Interview.
If you are planning to learn Data Structures and Algorithms.
If you desire to contribute to the open source community.
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