Module-1 - Notation Of Algorithm

Module-2 - Sorting and Searching Techniques

Module-3 - Greedy Techniques & Dynamic Programming Paradigm

Module-4 - String Matching Algorithms & Backtracking

Module-5 - Branch and Bound, Introduction to Computability & Approximation Algorithms

Design and Analysis of Algorithms (DAA) is a vast field that covers a range of algorithms, techniques, and concepts. If you're a beginner looking to get started with DAA, here are some fundamental topics and concepts you can focus on:

1. Algorithm Analysis:

- Understanding and analyzing the efficiency of algorithms.

- Time and space complexity analysis.

- Big O notation and asymptotic analysis.

2. Sorting Algorithms:

- Bubble sort, selection sort, insertion sort.

- Merge sort, quicksort, heapsort.

- Understanding their time complexity and when to use each algorithm.

3. Searching Algorithms:

- Linear search and binary search.

- Hashing and hash-based search algorithms.

- Understanding their time complexity and trade-offs.

4. Recursion:

- Understanding recursion and recursive algorithms.

- Recursive vs. iterative approaches.

- Solving problems using recursion.

5. Data Structures:

- Arrays, linked lists, stacks, queues.

- Trees (binary trees, binary search trees).

- Graphs (representation and traversal algorithms).

- Hash tables and hash-based data structures.

etc

It's important to combine theoretical understanding with practical implementation. Implementing and experimenting with algorithms in a programming language of your choice can enhance your understanding.

Remember to start with the basics and gradually build your knowledge and skills in DAA. Practicing problem-solving and analyzing different algorithms will help you develop a strong foundation in DAA as a beginner.

Module-1 - Notation Of Algorithm

Module-2 - Sorting and Searching Techniques

Module-3 - Greedy Techniques & Dynamic Programming Paradigm

Module-4 - String Matching Algorithms & Backtracking

Module-5 - Branch and Bound, Introduction to Computability & Approximation Algorithms

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