Design Algorithm & Analysis(DAA)

Learn Design Algorithm & Analysis(DAA) the exam way—clear concepts, worked examples, and 55 focused lessons in computer science study.

Instructor: DAKALA SREENIVASULU

Last updated Aug 2026 en

18 learners enrolled

all-levels

This course includes

— on-demand video
Access on mobile & desktop
Full lifetime access
Certificate of completion

Course content

8 sections · 55 lectures · 5 total hours

Lec-01: Introduction to Algorithm Preview
Lec-02 : Space Complexity | Algorithm Performance
Lec-03 : Time Complexity | Algorithm Performance
Lec-04 : Pseudo code - 1 | Sequence & Selection logic
Lec-05 : Pseudo code - 2 | Iteration logic

Lec-06 : Asymptotic notation | Introduction Preview
Lec-07 : Asymptotic growth
Lec-08 : Theta Notation | Asymptotic notation
Lec-09 : Big - O notation | Asymptotic notation
Lec-10 : Big Omega, Little oh & Omega | Asymptotic notation

Lec-11 : Divide & Conquer algorithm Preview
Lec-12 : Binary search Algorithm | Divide & Conquer
Lec-13 : Binary Search Example | Successful
Lec-14 : Binary Search Example | UnSuccessful
Lec-15 : Merge sort Algorithm | Divide & Conquer
Lec-16 : Merge Sort example | Divide & Conquer
Lec-17 : Quicksort algorithm | Divide & Conquer
Lec-18 : Quicksort Example | Divide & Conquer
Lec-19 : Matrix Multiplication example
Lec-20 : Matrix Multiplication example | Divide & Conquer
Lec-21 : Strassen's algorithm | Matrix Multiplication

Lec-22 : BST : Binary Search Tree Preview
Lec-23 : BST Traversal | Introduction
Lec-24 : BST : Inorder, Preorder & Post Order traversal
Lec-25 : Spanning Tree
Lec-26 : Prim's Algorithm | Minimum Spanning Tree
Lec-27 : Krushkal's Algorithm | Minimum Spanning Tree
Lec-28 : Prim's Vs Krushkal's algorithm | MST

Lec-29 : BFS : Breadth First Search Algorithm Preview
Lec-30 : BFS : Breadth First Search Example
Lec-31 : DFS : Depth First Search Algorithm
Lec-32 : DFS : Depth First Search Example

Lec-33 : AND/OR Graph Preview
Lec-34 : Connected Components | Graph
Lec-35 : Biconnected Components | Graph
Lec-36 : Dijkstra's algorithm | Shortest path
Lec-37 : Bellman Ford algorithm | Shortest path
Lec-38 : Greedy Method
Lec-39 : Job Sequencing problem with deadline | Greedy method
Lec-40 : Minimum Cost Spanning Tree algorithms | Greedy Method
Lec-41 : Minimum Cost Spanning Tree Examples | Greedy Method

Lec-42 : Dynamic Programming Preview
Lec-43 : Matrix chained multiplication | Dynamic Programming
Lec-44 : Matrix chained multiplication Example | Dynamic Programming
Lec-45 : All pairs Shortest Path Algorithm | Dynamic Programming
Lec-46 : All pairs shortest Path Example | Dynamic Programming
Lec-47 : 0/1 Knapsack Problem Algorithm | Dynamic Programming
Lec-48 : 0/1 Knapsack problem Example | Dynamic Programming
Lec-49 : Traveling Salesman Problem - 1 | Dynamic Programming
Lec-50 : Traveling Salesman Problem - 2 | Dynamic Programming
Lec-51 : Traveling Salesman Problem - 3 | Dynamic Programming

Lec-52 : Backtracking General method Preview
Lec-53 : N Queen problem | Backtracking
Lec-54 : Sum of Subset problem | Backtracking
Lec-55 : Hamiltonian Circuit Problem | Backtracking

Explore related topics

Computer Science all-levels

Description

Design Algorithm & Analysis(DAA) is an exam-focused computer science study programme designed for B.Tech / MCA learners and anyone revising CS subjects for semester exams (all levels). Lessons are paced for semester revision and competitive practice, with clear explanations you can replay anytime.

You will connect definitions to exam-style problems in Design Algorithm & Analysis(DAA), so you can write clearer answers, dry-run code mentally, and revise units in order. Syllabus highlights include Complexity, Notations, Divide & Conquer, BST & Spanning Trees, BFS & DFS, and Shortest path & Greedy Methods. Across 55 lessons, you will move from foundations to problem-solving patterns that show up in university papers and placement tests.

Taught by DAKALA SREENIVASULU, this course keeps theory short and practice heavy—so you can revise faster, spot examiner cues, and build confidence before mocks and finals.