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Data Structures and Algorithms

Master arrays, linked lists, trees, graphs, dynamic programming, and advanced problem-solving patterns through a structured 6-month learning plan with weekly contests, mock interviews, and company-specific preparation.

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

Curriculum

Module 1: Complexity Analysis & Problem-Solving Foundations

2 weeks

Topics Covered:

  • Time Complexity: Big-O, Big-Omega, Big-Theta Notations
  • Space Complexity & Auxiliary Space Analysis
  • Best Case, Worst Case & Average Case Analysis
  • Common Complexity Classes (O(1), O(log n), O(n), O(n log n), O(n²), O(2ⁿ))
  • Analyzing Loops, Nested Loops & Recursive Functions
  • Brute Force to Optimized Thinking Framework
  • Introduction to Problem-Solving Patterns
  • Edge-Case Identification & Handling
  • Setting Up Coding Environment (VS Code, Compiler, Debugger)
  • Math Refresher for DSA (Primes, GCD, LCM, Modular Arithmetic, Logarithms)

Projects:

  • Complexity Analysis Workbook (50+ Code Snippets)
  • Pattern Identification Problem Set

Module 2: Arrays, Strings & Two Pointers

3 weeks

Topics Covered:

  • Array Basics & In-Place Operations (Insert, Delete, Shift)
  • Two Pointer Technique (Opposite Direction, Same Direction, Fast & Slow)
  • Sliding Window Pattern (Fixed Size, Variable Size, At Most K, Exactly K)
  • Prefix Sum & Difference Arrays (1D & 2D)
  • Kadane's Algorithm & Maximum Subarray Variations
  • Dutch National Flag Algorithm & Partitioning
  • Rotating & Reversing Arrays
  • Merge Intervals Pattern
  • String Manipulation & Transformation
  • Palindrome Problems & Variations
  • Anagram Detection & Frequency Counting
  • String Matching Algorithms (Naive, KMP Introduction, Rabin-Karp Introduction)
  • Substring Search & Pattern Matching

Projects:

  • Sliding Window & Two Pointers Problem Workbook (30+ Problems)
  • Array Transformation Toolkit (Custom Implementation Library)

Module 3: Hashing, Sets & Maps

2 weeks

Topics Covered:

  • Hash Table Internal Working (Hash Functions, Collision Handling - Chaining & Open Addressing)
  • HashMap & HashSet Operations (Insert, Delete, Search - O(1) Average)
  • Frequency Counting & Counting Sort Pattern
  • Two Sum, Three Sum, Four Sum Variations
  • Subarray with Sum K (Prefix Sum + HashMap Optimization)
  • Longest Substring Without Repeating Characters
  • Group Anagrams & Custom Hashing
  • LRU Cache Implementation (HashMap + Doubly Linked List)
  • Ordered Map (TreeMap/C++ Map) Internal Working & Applications
  • Count Sort, Bucket Sort & Radix Sort Basics

Projects:

  • Custom HashMap Implementation from Scratch
  • LRU Cache System Design & Implementation
  • Hashing Problem Set (25+ Problems)

Module 4: Sorting, Searching & Divide & Conquer

3 weeks

Topics Covered:

  • Sorting Algorithms Deep Dive:
  • - Bubble Sort, Selection Sort, Insertion Sort (O(n²))
  • - Merge Sort (O(n log n), Stable, Divide & Conquer)
  • - Quick Sort (O(n log n) Average, Pivot Selection, Partition Schemes)
  • - Heap Sort (O(n log n), In-Place)
  • - Counting Sort, Bucket Sort, Radix Sort (Linear Time)
  • Sorting Stability, In-Place vs Extra Space Trade-offs
  • Custom Comparator Functions & Multi-Key Sorting
  • Binary Search Fundamentals & Variations:
  • - Classic Binary Search on Sorted Array
  • - Lower Bound & Upper Bound
  • - Search in Rotated Sorted Array
  • - Binary Search on Answer (Min/Max Problems)
  • - Binary Search on Real Numbers
  • Ternary Search Introduction
  • Divide & Conquer Paradigm:
  • - Merge Sort & Quick Sort as D&C Examples
  • - Power Function (Binary Exponentiation)
  • - Matrix Multiplication (Strassen's Introduction)

Projects:

  • Sorting Algorithm Visualizer (Console/Web)
  • Custom Sorting Library with Performance Comparison
  • Binary Search Problem Set (25+ Problems)

Module 5: Linked Lists

2 weeks

Topics Covered:

  • Singly Linked List (Node Structure, Traversal, Insertion, Deletion)
  • Doubly Linked List (Two-Way Traversal, Operations)
  • Circular Linked List (Detection, Operations)
  • Fast & Slow Pointer Technique (Floyd's Cycle Detection)
  • Finding Middle Node, Nth Node from End
  • Reversing a Linked List (Iterative & Recursive)
  • Detecting & Removing Cycles
  • Merging Two Sorted Lists
  • Intersection Point of Two Linked Lists
  • Clone List with Random Pointer (Deep Copy)
  • LRU Cache Implementation (LinkedHashMap/ Doubly Linked List + HashMap)
  • Linked List Based Stack & Queue
  • Skip List Introduction

Projects:

  • Complete Linked List Library (All Operations with Testing)
  • LRU Cache Implementation with Real-World Use Case
  • Polynomial Calculator using Linked Lists

Module 6: Stacks, Queues & Monotonic Patterns

2 weeks

Topics Covered:

  • Stack Basics (LIFO, Push, Pop, Peek, Implementation using Array & LL)
  • Stack Applications:
  • - Balanced Parentheses & Bracket Validation
  • - Expression Evaluation (Infix, Prefix, Postfix Conversion & Evaluation)
  • - Next Greater/Smaller Element
  • - Largest Rectangle in Histogram
  • - Stock Span Problem
  • Queue Basics (FIFO, Enqueue, Dequeue, Implementation)
  • Circular Queue & Deque (Double-Ended Queue)
  • Priority Queue Introduction (Heap-Based)
  • Monotonic Stack Pattern (Increasing & Decreasing)
  • Monotonic Queue (Sliding Window Maximum/Minimum)
  • Queue using Two Stacks & Vice Versa
  • Min Stack (Get Min in O(1))

Projects:

  • Expression Evaluator (Scientific Calculator)
  • Undo/Redo System using Stacks
  • Browser History (Back/Forward Navigation)

Module 7: Recursion & Backtracking

3 weeks

Topics Covered:

  • Recursive Thinking & Problem Decomposition
  • Base Case & Recursive Case Design
  • Recurrence Relations & Solving Methods (Substitution, Master Theorem Intro)
  • Recursion Tree Method
  • Tail Recursion & Optimization
  • Backtracking Template & State-Space Tree
  • Classic Backtracking Problems:
  • - N-Queens Problem
  • - Sudoku Solver
  • - Rat in a Maze
  • - Knight's Tour
  • - Word Search
  • Combinatorial Problems:
  • - Generating All Subsets (Power Set)
  • - Generating All Permutations
  • - Combination Sum & Variations
  • - Letter Combinations of Phone Number
  • State-Space Pruning & Optimization
  • Branch & Bound Introduction
  • Recursion to DP Conversion Basics

Projects:

  • Combinatorial Problem Solver (Subsets, Permutations, Combinations Generator)
  • Sudoku Solver & Generator Application
  • Maze Generator & Solver with Path Visualization

Module 8: Trees & Binary Search Trees

4 weeks

Topics Covered:

  • Tree Terminology (Root, Node, Leaf, Height, Depth, Level, Degree)
  • Binary Tree Representation (Array & Linked Representation)
  • Tree Traversals:
  • - Inorder, Preorder, Postorder (Recursive & Iterative)
  • - Level Order Traversal (BFS using Queue)
  • - Zigzag/Spiral Traversal
  • - Vertical Order Traversal
  • - Boundary Traversal
  • - Diagonal Traversal
  • Tree Properties (Count Nodes, Height, Diameter, Width)
  • Lowest Common Ancestor (LCA) - Multiple Approaches
  • Binary Search Tree (BST) Operations (Search, Insert, Delete)
  • BST Validation & Recovery
  • Balanced BST (AVL Trees - Rotations, Insertions, Deletions)
  • Red-Black Trees Introduction
  • Segment Tree (Construction, Range Queries, Point Updates)
  • Fenwick Tree / Binary Indexed Tree (BIT)
  • Trie (Prefix Tree) (Insert, Search, Prefix Search, Delete)
  • Suffix Tree & Suffix Array Introduction

Projects:

  • Tree Utilities Toolkit (All Traversals, LCA, Diameter Functions)
  • Auto-Complete System using Trie
  • Segment Tree Visualizer with Range Query Support
  • File System Representation using N-ary Tree

Module 9: Heap, Priority Queue & Greedy Algorithms

3 weeks

Topics Covered:

  • Binary Heap (Min-Heap & Max-Heap) Implementation
  • Heap Operations (Insert, Extract, Heapify, Build Heap - O(n))
  • Priority Queue Applications:
  • - Kth Largest/Smallest Element
  • - Top K Frequent Elements
  • - Merge K Sorted Lists/Arrays
  • - Median in a Stream (Two Heaps Pattern)
  • - Task Scheduler
  • Greedy Algorithm Paradigm & Proof Techniques
  • Classic Greedy Problems:
  • - Activity Selection / Interval Scheduling
  • - Fractional Knapsack
  • - Huffman Coding
  • - Job Sequencing with Deadlines
  • - Minimum Platforms Problem
  • - Coin Change (Greedy vs DP)
  • - Fractional Knapsack
  • Scheduling & Resource Allocation Patterns
  • Greedy vs Dynamic Programming (When to Use Which)

Projects:

  • Task Scheduler Simulator (CPU Scheduling)
  • Huffman Coding Compressor/Decompressor
  • Top K Frequent Items Tracker (Real-Time Analytics)

Module 10: Graphs & Graph Algorithms

4 weeks

Topics Covered:

  • Graph Representation (Adjacency Matrix, Adjacency List, Edge List)
  • Graph Types (Directed, Undirected, Weighted, Connected, Complete, Bipartite, DAG)
  • Graph Traversals:
  • - Breadth-First Search (BFS) & Applications (Shortest Path in Unweighted Graph, Level Order)
  • - Depth-First Search (DFS) & Applications (Cycle Detection, Connected Components)
  • Cycle Detection (Directed - DFS/Coloring, Undirected - DFS/Union Find)
  • Topological Sorting (Kahn's Algorithm - BFS, DFS-Based)
  • Shortest Path Algorithms:
  • - Dijkstra's Algorithm (Single Source, Non-Negative Weights, Heap Optimization)
  • - Bellman-Ford Algorithm (Handles Negative Weights, Detects Negative Cycles)
  • - Floyd-Warshall Algorithm (All-Pairs Shortest Path)
  • - Shortest Path in DAG (Topo Sort + Relaxation)
  • Minimum Spanning Tree (MST):
  • - Prim's Algorithm (Dense Graphs)
  • - Kruskal's Algorithm (Sparse Graphs, Union-Find Data Structure)
  • Union-Find / Disjoint Set Union (DSU) (Find, Union, Path Compression, Union by Rank)
  • Strongly Connected Components (Kosaraju's Algorithm, Tarjan's Introduction)
  • Bipartite Graph Check (BFS/DFS Coloring)
  • Articulation Points & Bridges (Tarjan's Algorithm Introduction)
  • Eulerian Path & Circuit
  • Hamiltonian Path Introduction

Projects:

  • Route Planner (Google Maps Style with Shortest Path)
  • Social Network Analyzer (Friends, Mutual Friends, Shortest Connection)
  • Network Connectivity Checker (Connected Components, Bridges)

Module 11: Dynamic Programming

5 weeks

Topics Covered:

  • DP Fundamentals & Problem Identification
  • Memoization (Top-Down) vs Tabulation (Bottom-Up)
  • DP State Design & Recurrence Relations
  • 1D DP Problems:
  • - Fibonacci, Climbing Stairs (Simple Recurrence)
  • - House Robber (Skip Pattern)
  • - Frog Jump (Min Cost Pattern)
  • - Decode Ways
  • 2D DP / Grid Problems:
  • - Grid Traveler / Unique Paths
  • - Minimum Path Sum
  • - Edit Distance (Levenshtein Distance)
  • - Longest Common Subsequence (LCS)
  • - Longest Common Substring
  • Subsequence Patterns:
  • - Longest Increasing Subsequence (LIS) - O(n²) & O(n log n)
  • - Subset Sum & Partition Equal Subset Sum
  • - Coin Change (Min Coins & Number of Ways)
  • - Rod Cutting & Unbounded Knapsack
  • - 0/1 Knapsack & Variations
  • String DP:
  • - Longest Palindromic Subsequence
  • - Longest Palindromic Substring
  • - Wildcard Matching & Regular Expression Matching
  • - Word Break
  • Advanced DP Patterns:
  • - DP on Trees (Diameter, Max Path Sum, LCA)
  • - DP on Subsets (Bitmask DP)
  • - DP with Bitmasking
  • - DP with Probability
  • - Digit DP Introduction
  • Optimization Techniques (Space Optimization, State Reduction)

Projects:

  • DP Problem Workbook (50+ Curated Problems with Solutions)
  • Text Diff Tool (Edit Distance Application)
  • Optimal Route Calculator with Constraints
  • Stock Trading Strategy Optimizer (Multiple Transactions)

Module 12: Advanced Topics & Interview Preparation

3 weeks

Topics Covered:

  • Bit Manipulation (Operators, Tricks, Common Patterns, Power of Two)
  • Mathematics for DSA (Sieve of Eratosthenes, Prime Factorization, Modular Exponentiation, Combinatorics)
  • Probability & Statistics in Algorithms
  • String Matching Algorithms (KMP, Z-Algorithm)
  • Randomized Algorithms Introduction
  • Company-Specific Problem Patterns:
  • - FAANG Style Problems (Google, Amazon, Meta, Apple, Netflix)
  • - Microsoft, Adobe, Uber Specific Patterns
  • - Indian Product Companies (Flipkart, Swiggy, Zomato, Ola, Paytm)
  • - Service Companies (TCS, Infosys, Wipro) Patterns
  • System Design Primer (For Coding Interviews)
  • Object-Oriented Design Problems
  • Mock Interviews (DSA Focused, Communication, Approach Explanation)
  • Whiteboard Coding Practice
  • Time Management During Contests & Interviews
  • Topic-Wise Revision Strategy
  • Cheat Sheet Preparation & Last-Minute Tips

Projects:

  • Timed Full-Length Mock Interview Simulation (3 Rounds)
  • Personal DSA Cheat Sheet (1-Page per Topic)
  • Company-Specific Problem Set Workbook
  • Final Assessment: 4-Hour Coding Marathon (Mixed Topics)

Learning Objectives

  • ✓Analyze time and space complexity of algorithms using Big-O, Omega, and Theta notations
  • ✓Design efficient solutions with clear time-space trade-offs for real-world problems
  • ✓Apply common algorithmic patterns (Sliding Window, Two Pointers, Fast & Slow Pointers) to new problems
  • ✓Implement and test classical data structures from scratch (Linked Lists, Trees, Graphs, Heaps, Tries)
  • ✓Master advanced techniques: Dynamic Programming, Backtracking, Greedy, and Divide & Conquer
  • ✓Approach medium-to-advanced coding questions methodically using structured problem-solving frameworks
  • ✓Write readable, optimized, and well-documented solutions following coding best practices
  • ✓Perform confidently in technical interviews with clear communication and whiteboarding skills

Course Overview

The Data Structures and Algorithms course is a rigorous 6-month program designed to transform you from a basic programmer into a confident problem solver ready for top technical interviews. This isn't about memorizing solutions — it's about building deep pattern recognition and analytical thinking.

What Makes This DSA Course Different?

  • Pattern-Based Learning: Every problem is categorized into patterns (Sliding Window, Two Pointers, Fast & Slow, DP on Subsequences, etc.) so you learn to solve unseen problems.
  • 250+ Curated Problems: Each topic comes with handpicked problems arranged from easy to hard, covering all variations.
  • Weekly Contests: Timed contests every Sunday simulate real interview and competitive programming pressure.
  • 1:1 Mentorship Sessions: Monthly 1:1 sessions to review progress, identify weak areas, and adjust your learning path.
  • Company-Specific Preparation: Dedicated module covering patterns for FAANG, Indian product companies, and service companies.
  • Mock Interviews: 3 mock interviews with detailed feedback on problem-solving approach, communication, and code quality.
  • Language Flexibility: Follow along in C++, Java, or Python with language-specific tips and STL/Collections coverage.

Who Should Enroll?

This course is perfect for:

  • College Students (BTech, BCA, MCA) preparing for campus placements and internships.
  • Working Professionals preparing for job switches to product-based companies.
  • Competitive Programmers wanting structured practice across all topics.
  • Self-Taught Developers who know coding but need formal DSA training.
  • Anyone targeting companies like Google, Amazon, Microsoft, Flipkart, Uber, Swiggy, and more.

Prerequisites: Basic programming knowledge in C++, Java, or Python (loops, functions, arrays, basic syntax).

Course Structure

Learning Flow

  • Concept Sessions (30%): Deep dive into data structure internals and algorithm design.
  • Problem Solving (50%): Live problem-solving with step-by-step approach explanation.
  • Practice & Contests (20%): Assigned problem sets, weekly contests, and peer discussions.

Weekly Schedule

  • 3 Concept & Problem-Solving Sessions (60-90 min each)
  • 1 Doubt Clearing Session (60 min)
  • 1 Weekly Contest (90 min, Sunday)
  • Daily Problem Assignments (1-2 problems/day)

Progress Tracking

  • Module-wise topic tests
  • Monthly progress reports
  • Solved problems count tracking
  • Contest rating tracking
  • Weak area identification

What You'll Build

Implementation Projects

  • Custom HashMap — Build a hash table from scratch with collision handling
  • LRU Cache System — HashMap + Doubly Linked List implementation
  • Expression Evaluator — Scientific calculator supporting infix/postfix
  • Sorting Algorithm Visualizer — See algorithms in action
  • Auto-Complete System — Trie-based search suggestion engine
  • Route Planner — Shortest path finder like Google Maps
  • Huffman Coding Compressor — File compression/decompression tool
  • Sudoku Solver & Generator — Backtracking in action

Problem Workbooks

  • Sliding Window & Two Pointers Workbook (30+ Problems)
  • Binary Search Problem Set (25+ Problems)
  • Recursion & Backtracking Workbook (25+ Problems)
  • DP Problem Workbook (50+ Curated Problems)
  • Company-Specific Problem Sets

Career Impact

After completing this course, you'll be prepared for:

Target Companies & CTC Ranges

  • FAANG (₹25-60 LPA): Google, Amazon, Meta, Apple, Netflix, Microsoft
  • Product Companies (₹15-35 LPA): Flipkart, Swiggy, Zomato, Uber, Ola, Paytm, PhonePe, Cred
  • Startups (₹10-25 LPA): Zepto, Groww, Razorpay, Meesho, ShareChat
  • Service Companies (₹4-8 LPA): TCS, Infosys, Wipro, Accenture, Cognizant

Interview Success Rate

Our structured approach has helped students crack interviews at:

  • Amazon (SDE-1, SDE-2)
  • Microsoft (SDE, Senior SDE)
  • Google (L3, L4)
  • Flipkart, Swiggy, Uber, and more

Course Includes

  • 250+ Curated Problems with solutions and explanations
  • Weekly Contests with leaderboard and editorial solutions
  • 3 Mock Interviews with detailed feedback report
  • Monthly 1:1 Mentorship sessions (30 min each)
  • Topic-Wise Notes & Cheat Sheets for quick revision
  • Access to Private Discord Community for doubt solving
  • Company-Specific Question Banks (Amazon, Google, Microsoft, Flipkart, etc.)
  • Language-Specific Code Templates (C++, Java, Python)
  • Certificate of Completion

Fee Structure

Course Fee: ₹25,000 (6 months)

Payment Options:

  1. One-time Payment: ₹22,000 (₹3,000 discount)
  2. Quarterly: ₹12,500 × 2 installments
  3. Monthly: ₹4,167 × 6 installments

What's Included:

  • All sessions (live + recorded) for lifetime access
  • Weekly contests with editorial solutions
  • 3 mock interviews with feedback
  • Monthly 1:1 mentorship (30 min each)
  • Problem sets, notes, and cheat sheets
  • Certificate upon completion

Success Stories

"The pattern-based approach changed how I solve problems. I used to panic seeing new problems. Now I can identify the pattern and at least get a brute force solution within minutes. Cracked Amazon SDE-1!" — Rahul Kumar., SDE at Amazon

"I was stuck at 5 LPA in a service company. After completing this DSA course and 3 months of consistent practice, I switched to a product company at 18 LPA. The weekly contests and mock interviews were game-changers." — Priya Singh., SDE-2 at Flipkart

"The mentorship sessions helped me identify my weak areas (DP and Graphs). The structured practice plan and company-specific preparation got me through Google interviews." — Amit Verma., Software Engineer at Google

Frequently Asked Questions

Which programming language should I use?

You can choose C++, Java, or Python. C++ is recommended for its STL library and performance, but Java and Python are equally supported. Language-specific tips and STL/Collections coverage are provided for all three.

How many problems will I solve during the course?

You'll solve 250+ handpicked problems during sessions and assignments. Additionally, weekly contests expose you to 4-6 new problems each week, totaling 350+ problems over 6 months.

Is this course suitable for complete beginners in DSA?

Yes! The course starts from fundamentals (Big-O notation, arrays) and builds up to advanced topics (DP, Graph algorithms). You need basic programming knowledge (loops, functions, arrays) in one language.

How is this different from free YouTube resources?

Unlike free resources, this course provides: (1) Structured learning path with pattern-based classification, (2) Weekly contests for practice, (3) 1:1 mentorship to identify and fix weak areas, (4) Mock interviews with feedback, (5) Company-specific preparation, and (6) Accountability through progress tracking.

What if I miss a live session?

All sessions are recorded and available for lifetime access. You can watch them at your convenience and ask doubts in the next doubt-clearing session or on Discord.

Can I get placement assistance?

While this is a DSA course (not a placement guarantee program), we provide: mock interviews, company-specific problem sets, referral guidance, and connect top performers with hiring partners.

How much time should I dedicate daily?

Consistency is key. We recommend 2-3 hours daily: 60-90 minutes for concept sessions, and 1-2 hours for solving assigned problems. Weekend contests take 90 minutes.

Tags

Data StructuresAlgorithmsProblem SolvingComplexity AnalysisDynamic ProgrammingGraph AlgorithmsInterview PreparationCompetitive Programming

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