Data Structures & Algorithms (DSA) – 3 Week Course Outline
Target Audience: Beginners with basic programming knowledge seeking to master DSA concepts and improve their problem-solving skills.
Course Goals:
- Understand fundamental data structures: Arrays, Linked Lists, Stacks, Queues, Trees, Graphs, Hash Tables.
- Implement algorithms for common tasks: Searching, Sorting, Recursion, Dynamic Programming.
- Analyze time and space complexity: Learn Big O notation to measure algorithm efficiency.
- Develop problem-solving strategies: Practice applying DSA concepts to solve real-world problems.
Course Structure: Weekly modules with video lectures, interactive exercises, practice problems, quizzes, and forum discussions.
Week 1: Foundations & Arrays
- Day 1: Introduction to Algorithms and Data Structures
- What are algorithms? Types of algorithms (searching, sorting)
- Why learn DSA? Applications in competitive programming and interviews
- Basic Programming Concepts (Variables, Loops, Conditional Statements)
- Day 2-3: Arrays
- Array Representation & Operations (Insertion, Deletion, Searching)
- Traversal Techniques (Iterative vs. Recursive)
- Time Complexity Analysis of Array Operations
- Day 4-5: Sorting Algorithms
- Introduction to Sorting Algorithms (Bubble Sort, Insertion Sort)
- Implementation and Analysis of Time Complexity for Basic Sorts
- Practice Problems: Implementing and comparing different sorting algorithms.
Week 2: Linked Lists & Trees
- Day 1-3: Linked Lists
- Types of Linked Lists (Singly, Doubly, Circular)
- Operations on Linked Lists (Insertion, Deletion, Search)
- Applications of Linked Lists (Implement Stacks and Queues)
- Day 4-5: Trees
- Tree Structure & Terminology (Root, Node, Leaf, Branch)
- Binary Trees: Traversal Techniques (Inorder, Preorder, Postorder)
- Height and Level of Nodes in a Tree
Week 3: Graphs & Advanced Topics
- Day 1-2: Graphs
- Graph Representation (Adjacency Matrix, Adjacency List)
- Basic Graph Algorithms (Breadth First Search, Depth First Search)
- Applications of Graphs (Social Networks, Navigation Systems)
- Day 3-4: Hash Tables & Dynamic Programming
- Hashing Techniques and Collision Resolution
- Applications of Hash Tables (Caching, Data Retrieval)
- Introduction to Dynamic Programming (Solving Problems Recursively with Optimization)
- Day 5: Review & Mock Interview
- Comprehensive review of key concepts from all weeks.
- Simulated technical interview environment with common DSA questions.