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Data Structures and Algorithms

Master arrays, linked lists, trees, graphs, dynamic programming, and problem-solving patterns through a disciplined 6-month learning plan.

Duration: 6 months
Mode: online/offline
Language: Hindi/English
View Curriculum

Curriculum

Module 1: Complexity and Problem-Solving Foundations

2 weeks

Topics Covered:

  • Big-O fundamentals
  • Brute force to optimized thinking
  • Two-pointer and sliding window intuition
  • Edge-case analysis

Projects:

  • Pattern-based problem workbook

Module 2: Arrays, Strings, and Hashing

3 weeks

Topics Covered:

  • Array transformation patterns
  • Hash maps and frequency techniques
  • Prefix and suffix methods
  • String manipulation strategies

Projects:

  • Data processing challenge set

Module 3: Linked Lists, Stacks, and Queues

3 weeks

Topics Covered:

  • Linked list operations
  • Stack-based parsing
  • Queue and deque applications
  • Monotonic stack intro

Projects:

  • Expression evaluator

Module 4: Recursion and Backtracking

3 weeks

Topics Covered:

  • Recursive decomposition
  • Backtracking template
  • State-space pruning
  • Classic recursion problems

Projects:

  • Combinatorial problem solver

Module 5: Trees and Binary Search Trees

4 weeks

Topics Covered:

  • Tree traversals
  • BST operations
  • Tree depth and diameter
  • LCA and tree transformations

Projects:

  • Tree utilities toolkit

Module 6: Heap, Priority Queue, and Greedy

3 weeks

Topics Covered:

  • Heap operations
  • Top-k problems
  • Greedy selection logic
  • Scheduling patterns

Projects:

  • Scheduler simulator

Module 7: Graphs and Traversal Algorithms

4 weeks

Topics Covered:

  • Graph representation
  • BFS and DFS
  • Shortest path basics
  • Topological sorting

Projects:

  • Route planner

Module 8: Dynamic Programming

4 weeks

Topics Covered:

  • DP state design
  • Memoization and tabulation
  • Subsequence patterns
  • Optimization DP

Projects:

  • DP challenge workbook

Module 9: Interview Simulation and Final Assessment

2 weeks

Topics Covered:

  • Problem interpretation speed
  • Whiteboard communication
  • Optimization walkthrough
  • Solution quality review

Projects:

  • Timed problem-solving evaluation

Learning Objectives

  • ✓Design efficient solutions with clear time-space trade-offs
  • ✓Apply common algorithmic patterns to new problems
  • ✓Implement and test classical data structures
  • ✓Approach medium-to-advanced coding questions methodically
  • ✓Write readable and optimized solutions

Course Overview

This 6-month DSA course is structured for consistent skill growth, not random question solving. Every module emphasizes how to identify patterns, choose the right data structure, and explain optimization clearly.

You work on topic-focused problem sets and milestone assessments so your progress stays measurable.

Best Fit For

  • Students preparing for technical interviews
  • Learners who need stronger algorithmic fundamentals
  • Developers who want better problem-solving speed and clarity

Frequently Asked Questions

Can I join with Python instead of C++?

Yes. You can follow the full course with C++, Java, or Python.

Is this purely theoretical?

No. The course is practice-heavy with guided problem sets, evaluations, and implementation-focused sessions.

How is progress tracked?

Progress is tracked through module assessments, timed practice sets, and final interview-style evaluations.

Tags

Data StructuresAlgorithmsProblem SolvingComplexity Analysis

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