Data Structures and Algorithms in Java: Master Problem Solving and Coding
Develop the skills to build efficient algorithms and manage data effectively using Java. This course gives you practical experience in designing, analyzing, and implementing complex data structures to solve real-world problems.
Data structures and algorithms are the foundation of robust software engineering and technical interviews. This course walks you through arrays, trees, graphs, and dynamic programming techniques that make your code scalable. Gain the confidence to ace coding interviews and write highly optimized programs.
What You'll Learn
- ✓Understand core DSA concepts like time and space complexity analysis.
- ✓Implement foundational linear data structures like linked lists, stacks, and queues.
- ✓Master non-linear data structures including trees, heaps, and graphs.
- ✓Learn to optimize code using advanced searching and sorting algorithms.
- ✓Apply advanced techniques like dynamic programming and greedy algorithms.
- ✓Build problem-solving skills to crack top-tier technical interviews.
Course Curriculum
Understand the fundamentals of Java and algorithmic efficiency.
- Java Refresher: OOP concepts, Generics, and Collections
- Introduction to Algorithm Analysis and Big O Notation
- Time and Space Complexity calculations
- Asymptotic Notations: Big O, Theta, and Omega
- Setting up the development environment (IntelliJ IDEA)
Master the manipulation of contiguous memory data structures.
- 1D and 2D Arrays: Traversal, insertion, and deletion
- String manipulation and pattern matching basics
- Sliding Window and Two-Pointer techniques
- Matrix operations and structural traversals
- Solving classic algorithmic puzzles (e.g., Trapping Rain Water)
Learn foundational linear data structures and their applications.
- Singly, Doubly, and Circular Linked Lists
- Implementing Stacks using Arrays and Linked Lists
- Queue and Circular Queue implementations
- Applications: Balanced Parentheses, Next Greater Element
- Hands-on: Designing a custom LRU Cache
Explore hierarchical data structures and traversal methods.
- Tree terminology and mathematical properties
- Binary Tree traversals: Inorder, Preorder, Postorder
- Binary Search Tree (BST) operations: Insertion, Searching
- Lowest Common Ancestor and Tree Height problems
- Introduction to balanced trees (AVL and Red-Black Trees)
Optimize search operations and implement priority-based systems.
- Hashing concepts: Hash Maps, Hash Sets, and Collisions
- Min Heap and Max Heap implementations
- Priority Queue applications in Java
- Trie data structure for efficient string searches
- Project: Building an autocomplete suggestion engine
Model real-world networks using vertices and connected edges.
- Graph representation: Adjacency Matrix and Adjacency List
- Breadth-First Search (BFS) and Depth-First Search (DFS)
- Cycle detection in directed and undirected graphs
- Topological Sorting and its dependency applications
- Hands-on: Finding connected components in a network
Solve complex routing and network optimization problems.
- Dijkstra's Algorithm for single-source shortest paths
- Bellman-Ford and Floyd-Warshall Algorithms
- Minimum Spanning Trees (MST) principles
- Prim's and Kruskal's Algorithms
- Disjoint Set Union (DSU) and Path Compression
Master advanced problem-solving paradigms for algorithmic optimization.
- Introduction to Recursion and Backtracking strategies
- Memoization vs. Tabulation (Top-Down vs. Bottom-Up DP)
- Classic DP Problems: Knapsack, Longest Common Subsequence
- Greedy Approach fundamentals and activity selection
- Capstone: Solving advanced competitive programming challenges
Course Materials Provided
- ✓In-Depth Video Lessons: Comprehensive video content covering all major data structures and algorithms.
- ✓Hands-On Projects: Use coding challenges to build strong problem-solving logic in Java.
- ✓Access to Resources: Get downloadable code templates, cheat sheets, and problem sets.
- ✓Knowledge Checks: Test your understanding with algorithmic quizzes after each module.
- ✓Industry Expert Insights: Learn technical interview strategies from top tech professionals.
Who This Course Is For
- ✓Beginners: Individuals with basic programming knowledge who want to build a strong computer science foundation.
- ✓Students: Computer Science students preparing for academics, coding competitions, or campus placements.
- ✓Professionals: Software developers looking to refine their algorithmic thinking and optimize existing codebases.
- ✓Job Seekers: Candidates actively preparing for technical interviews at top-tier product-based software companies.
