Design and Analysis of Algorithms Lecture Notes – Complete Series

Access complete DAA lecture notes with explanations, examples and algorithms. Covers introduction, fundamentals of problem solving, recursion, algorithm design techniques, complexity analysis and more.

Introduction

Design and Analysis of Algorithms is a core subject in computer science and engineering. This series of lectures provides structured, easy-to-follow notes on algorithms, their properties, problem-solving frameworks, recursive methods, complexity analysis and design techniques.

Whether you’re a student preparing for exams, a beginner in competitive programming or someone brushing up on computer science fundamentals, these lecture notes will give you a clear understanding of algorithms from the ground up.

Table of Contents – DAA Lecture Notes

Lecture – Introduction to Algorithms

Read Lecture: Introduction to Design and Analysis of Algorithms
Covers: Definition of algorithms, role in computing, characteristics of a good algorithm, algorithm vs program, examples like decimal to binary conversion, and sorting basics.

Lecture – Fundamentals of Algorithmic Problem Solving

Read Lecture: Fundamentals of Algorithmic Problem Solving
Covers: Framework for algorithm design, problem understanding, developing models, design techniques, proving correctness, complexity analysis, and examples like unique elements in arrays and minimum difference problems.

Lecture – Top-Down Design and Recursive Algorithms

Read Lecture: Top-Down Design and Recursive Algorithms
Covers: Top-down design method, recursion basics, base and recursive cases, recursive examples (power, factorial), recursion vs iteration comparison, and when to use recursion.

Lecture –Advanced Analysis of Algorithms

Read Lecture : Advance analysis of algorithms
Covers: Covers advanced analysis of algorithms in DAA. Learn about time and space complexity, asymptotic notations (Big-O, Ω, Θ), performance classes, growth rates and complexity examples with code.

What You’ll Learn from This DAA Series

• How to design efficient algorithms for real-world problems

• Different algorithm design paradigms (brute force, divide and conquer, greedy, dynamic programming, backtracking)

• How to prove correctness and analyze efficiency of algorithms

• Examples of recursive algorithms and when to use them

• Practical applications for competitive programming and coding interviews

Why Follow This Series?

Structured lecture-by-lecture coverage
Includes examples, pseudocode, and flowcharts
Useful for students, teachers, and self-learners

Next Lectures Coming Soon

• Lecture 4: Divide and Conquer Techniques

• Lecture 5: Greedy Algorithms

• Lecture 6: Dynamic Programming

• Lecture 7: Graph Algorithms

• …and more!