Name: Algorithm Design Techniques From beginner to advanced (DAA)
Rating: 4.0 (32 reviews)

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Last updated 5/2020

English

What you'll learn

Analyze a given algorithm and express its time and space complexities in asymptotic notations.
Solve recurrence equations using Iteration Method, Recurrence Tree Method and Master’s Theorem.
Design algorithms using Divide and Conquer Strategy.
Compare Dynamic Programming and Divide and Conquer Strategies.
Solve Optimization problems using Greedy strategy.
Design efficient algorithms using Back Tracking and Branch Bound Techniques for solving problems.
Learn the fundamentals of complexity theory

Course content

17 sections • 102 lectures • 8h 26m total length

Course Over view3:13
Will give you an overview of the course
Math Fundamentals4:16
You must be strong in arithmetic, geometric and logarithmic series before continuing to other lectures.
Introduction1:15
What is algorithm and why we are analyzing algorithms?
Space Complexity7:23
Space complexity

//As you know behind every efficient software there will be an efficient algorithm.

But how do you build an efficient algorithm?

You can choose any of the design techniques such as Divide and Conquer, Dynamic Programming, Greedy Approach, Back Tracking & Branch and Bound.

From the technique listed above which one is suitable for your program/problem?

Take this course then you will be able to choose the right one.

/* This course is for both students and professionals */