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LEARN WITH A CLEAR DIRECTION

Data Structures

Master the building blocks of computer science — understand how data is stored, accessed, and organized through every major data structure, from arrays to graphs.

Beginner to IntermediateSelf-paced10 modules55 available lessons

Your path, one skill at a time.

Data Structures are the foundation of all software systems. This roadmap takes you from the basics of how data is stored in memory to complex structures like graphs and tries. You’ll learn conceptual depth, visual intuition, memory layouts, trade-offs, and practical use cases across software engineering and system design.

What you’ll learn

  • Understand internal memory representation of core data structures
  • Know which data structure to use for specific real-world problems
  • Visualize how data is stored, linked, and traversed
  • Evaluate time and space trade-offs
  • Implement efficient storage and retrieval mechanisms conceptually
  • Build a strong base for learning algorithms later

THE CURRICULUM

Build your knowledge, step by step.

55 lessons across 10 modules. Open a module to explore its lessons and practical work.

01MODULE 01Foundations of Data Structures5 lessons · Self-paced

What data structures are, how memory works, and why they matter.

  1. 01What is a Data Structure?15 min
  2. 02Static vs Dynamic Data Structures20 min
  3. 03Memory Layout: Stack, Heap, Pointers25 min
  4. 04Abstract Data Types (ADT) vs Data Structures15 min
  5. 05Practice: Identify Data Structures in Real Systems40 min
02MODULE 02Arrays and Memory Representation6 lessons · Self-paced

Understanding sequential storage and index-based access.

  1. 01Array Basics and Fixed Memory Allocation25 min
  2. 02Indexing, Contiguity, and Cache Locality20 min
  3. 03Multidimensional Arrays and Memory Mapping22 min
  4. 04Dynamic Arrays and Resizing Conceptually20 min
  5. 05Use Cases: Images, Tables, and Buffers15 min
  6. 06Visualization Exercise: Array Indexing30 min
03MODULE 03Linked Lists6 lessons · Self-paced

Non-contiguous storage and node-based structures.

  1. 01Nodes, Links, and Memory References25 min
  2. 02Singly vs Doubly Linked Lists25 min
  3. 03Circular Lists and Sentinel Nodes22 min
  4. 04Advantages and Drawbacks vs Arrays15 min
  5. 05Use Cases: Undo Feature, Music Playlists, Hash Chains20 min
  6. 06Visualization Exercise: Pointer Traversal35 min
04MODULE 04Stacks and Queues5 lessons · Self-paced

Ordered data control for last-in-first-out (LIFO) and first-in-first-out (FIFO) behaviors.

  1. 01Stack Concept and Push/Pop Operations20 min
  2. 02Queue Concept and Enqueue/Dequeue20 min
  3. 03Circular Queues and Deques25 min
  4. 04Practical Applications (Call Stack, Job Scheduling)20 min
  5. 05Visualization: Simulate Stack and Queue Operations30 min
05MODULE 05Hash Tables and Dictionaries6 lessons · Self-paced

Fast access through hashing and key-value mapping.

  1. 01Concept of Hashing and Hash Functions25 min
  2. 02Collision Handling (Chaining, Open Addressing)25 min
  3. 03Load Factor and Rehashing20 min
  4. 04Advantages, Limitations, and Use Cases15 min
  5. 05Real-World Uses: Caches, Maps, Sets20 min
  6. 06Visualization Exercise: Hash Distribution35 min
06MODULE 06Trees6 lessons · Self-paced

Hierarchical structures that organize data in parent–child relationships.

  1. 01Tree Terminology (Root, Leaf, Height, Degree)20 min
  2. 02Binary Trees and Traversal Orders25 min
  3. 03General Trees and N-ary Trees22 min
  4. 04Balanced Trees Concept (Height Balancing)25 min
  5. 05Applications: File Systems, DOM, Organization Charts20 min
  6. 06Visualization: Tree Traversal Paths35 min
07MODULE 07Heaps and Priority Structures5 lessons · Self-paced

Specialized trees that maintain priority ordering.

  1. 01Heap Properties and Hierarchical Structure25 min
  2. 02Min-Heaps vs Max-Heaps20 min
  3. 03Heap Representation Using Arrays20 min
  4. 04Applications: Scheduling, Leaderboards, Caching20 min
  5. 05Visualization Exercise: Heap Tree Construction35 min
08MODULE 08Graphs5 lessons · Self-paced

Networks of nodes and edges — the most powerful structure for modeling relationships.

  1. 01Graph Basics: Vertices, Edges, and Adjacency25 min
  2. 02Graph Representations: Matrix and List25 min
  3. 03Directed vs Undirected, Weighted vs Unweighted20 min
  4. 04Real-World Applications: Maps, Social Networks, Dependencies20 min
  5. 05Visualization: Draw and Analyze Graphs40 min
09MODULE 09Advanced and Specialized Structures6 lessons · Self-paced

Data structures built for high performance and domain-specific needs.

  1. 01Tries (Prefix Trees) and Their Use Cases25 min
  2. 02Disjoint Set (Union-Find) Concept25 min
  3. 03Sparse Tables and Segment Trees Overview30 min
  4. 04Bloom Filters and Bitmaps25 min
  5. 05Practical Applications Across Domains20 min
  6. 06Visualization Exercise: Tries and Sets40 min
10MODULE 10Case Studies and Real-World Applications5 lessons · Self-paced

How real systems leverage these structures.

  1. 01Databases and Indexing (B-Trees, Hash Maps)30 min
  2. 02Operating Systems: Queues, Linked Lists, Trees25 min
  3. 03Web Browsers, Compilers, and File Systems25 min
  4. 04Designing Data Models in Real Products30 min
  5. 05Capstone: Visualize a Real System’s Data Flow45 min