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Programming • Intermediate

Abdul Bari DSA Course

Understand core data structures and algorithmic paradigms with clear visual proofs, complexity analysis, and problem solving.

60 Hours Duration
English Language
Money Mitra Network Official Certification

Course Overview

Learn Data Structures & Algorithms with Abdul Bari's renowned pedagogical style. Deep dive into asymptotic analysis, recursion, trees, graphs, sorting, searching, greedy algorithms, and dynamic programming.

What You'll Learn

  • Analyze Big-O time and space complexity for recursive and iterative algorithms
  • Implement Arrays, Linked Lists, Stacks, Queues, Binary Trees, and Heaps
  • Master Graph traversal algorithms (BFS, DFS, Dijkstra, Kruskal, Prim)
  • Solve complex dynamic programming and divide-and-conquer problems

Key Skills Covered

Data StructuresAlgorithmsDynamic ProgrammingTime & Space Complexity

Structured Learning Roadmap

Step-by-step milestone progression for Abdul Bari DSA Course

4 Milestone Phases
1
Phase 1 • Foundations & Environment Setup
Core Fundamentals & Tooling Initialization

Establish prerequisite knowledge in Programming, setup local development environments, and master fundamental syntax and concepts.

Target Milestone: Gain confidence with prerequisite concepts: Knowledge of any programming language (C, C++, Java, or Python).
2
Phase 2 • Core Skills & Technical Execution
Module 1: Asymptotic Analysis & Recursion & Module 2: Linear Data Structures

Big-O, Big-Omega, recurrence relations, recursion trees, and Master Theorem. Dynamic arrays, doubly linked lists, stack operations, and queue implementations.

Target Milestone: Build hands-on technical proficiency in key skills: Data Structures, Algorithms.
3
Phase 3 • Advanced Application & Practical Labs
Module 3: Non-Linear Data Structures (Trees & Graphs) & Module 4: Dynamic Programming & Greedy Approach

BST, AVL Trees, Heap sort, BFS, DFS, and shortest path algorithms. Knapsack problem, Longest Common Subsequence, matrix chain multiplication.

Target Milestone: Master advanced problem solving in: Dynamic Programming, Time & Space Complexity.
4
Phase 4 • Capstone, Certification & Career Track
Real-World Project Build & MMN Credentialing

Synthesize all course modules into a production-grade portfolio project, undergo self-assessment quizzes, and earn your official Money Mitra Network certificate.

Target Milestone: Achieve job-ready proficiency: Analyze Big-O time and space complexity for recursive and iterative algorithms.

Course Curriculum

Module 1: Asymptotic Analysis & Recursion
Big-O, Big-Omega, recurrence relations, recursion trees, and Master Theorem.
Module 2: Linear Data Structures
Dynamic arrays, doubly linked lists, stack operations, and queue implementations.
Module 3: Non-Linear Data Structures (Trees & Graphs)
BST, AVL Trees, Heap sort, BFS, DFS, and shortest path algorithms.
Module 4: Dynamic Programming & Greedy Approach
Knapsack problem, Longest Common Subsequence, matrix chain multiplication.

Instructor Profile

RK

Rohan Kulkarni

Principal Full-Stack Architect & Engineering Mentor

Ex-Big Tech software architect with 11+ years building high-throughput web applications, microservices, and mobile platforms.

⭐ 4.9 Rating 👥 28,000+ Enrolled Students 🎓 MMN Certified Lead

Prerequisites & Audience

Prerequisites

Knowledge of any programming language (C, C++, Java, or Python).

Who This Course Is For

Computer Science students, software engineering applicants, and GATE exam candidates.

Frequently Asked Questions

How do I access the course material after purchase?
Upon completion of checkout, you receive instant lifetime access to the full course module repository on the Money Mitra Network learning platform.
Is there a certificate of completion included?
Yes, completing all module quizzes and project milestones issues an official Money Mitra Network certificate with a verifiable credential link.
What is the course refund policy?
We back all course purchases with a 7-day money-back guarantee if you are not completely satisfied with the course structure or content.

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