The data structure is a particular way of storing and organizing data so that it can be used efficiently. Arrays, trees, linked lists, stacks, graphs, etc. are all data structures and each of them allows us to perform different operations on data. No matter which programming language we use, it is important to learn algorithm design techniques in data structures in order to be able to build scalable systems. Selecting a proper design technique for algorithms is a complex but important task.

In this “Algorithm Design Techniques – Data Structure and Algorithms” you will learn about the following topics:

- Introduction to Algorithm
Design Techniques
- Brute-Force Or Exhaustive
Search
- What
Is The Use Of A Brute Force Algorithm?, Performance of Brute Force Algorithms, How
to Make a Brute Force Algorithm?
- Divide and Conquer
- Fundamental of Divide &
Conquer Strategy, Applications of Divide and Conquer Approach, Advantages of
Divide and Conquer, Disadvantages of Divide and Conquer
- Greedy Algorithms
- When to use Greedy Algorithms? Standard
Greedy Algorithm, Advantages of Greedy Approach/Technique, Disadvantages of
Greedy Approach/Technique
- Dynamic Programming
- Characteristics of Dynamic
Programming, Elements of Dynamic Programming, Components of Dynamic Programming,
Development of Dynamic Programming Algorithm, Applications of Dynamic
Programming
- Branch and Bounce Algorithms
- When Branch and Bound Is a Good
Choice? Branch and Bound Algorithm Pseudocode, Advantages of Branch and Bound Algorithm, Disadvantages of Branch and Bound Algorithm
- Randomized Algorithms
- When Is
Randomness Useful? How To Analyze Randomized Algorithms?
- Backtracking
Algorithm
- Example
of Backtracking Algorithm, Algorithm of Backtracking

==== Point to Note ====

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## BCA 3rd Semester Data Structure and Algorithms (DSA) Notes Pdf:

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