Advanced Data Structures
Master complex data structures and algorithms for technical interviews and real-world applications.
8 weeks
Intermediate
1,245 students
4.8 (256 reviews)
Rohit Negi
Ex Uber
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24 video lessons (48
hours)
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12 coding assignments
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4 real-world projects
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1-on-1 mentor sessions
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Certificate of completion
- Lifetime access
30-day money-back
guarantee
Course Overview
This comprehensive course on Advanced Data Structures is designed for software engineers and computer science students who want to deepen their understanding of complex data structures and algorithms.
Whether you're preparing for technical interviews at top tech companies or looking to improve your problem-solving skills for real-world applications, this course will provide you with the knowledge and practice you need.
What You'll Learn
- Advanced tree structures (Red-Black Trees, AVL Trees, B-Trees)
- Graph algorithms and optimizations
- Advanced hash table implementations
- Heap variations and priority queues
- Trie structures and applications
- Segment trees and Fenwick trees
- Disjoint set data structures
- Time and space complexity analysis
Prerequisites
To get the most out of this course, you should have:
- Basic knowledge of data structures (arrays, linked lists, stacks, queues)
- Familiarity with at least one programming language (Java, Python, C++, or JavaScript)
- Understanding of basic algorithm concepts (sorting, searching)
Projects You'll Build
Pathfinding Visualizer
Build a web-based tool to visualize graph algorithms like Dijkstra's and A*.
In-Memory Database
Implement a simple in-memory database with efficient indexing structures.
Search Engine
Create a mini search engine using tries and inverted indices.
Social Network Analyzer
Build a tool to analyze social network data using graph algorithms.
Course Curriculum
This 8-week course is divided into modules, each focusing on specific data structures and algorithms.
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Binary Search Trees Revisited
Review of BST operations and analysis
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AVL Trees: Self-Balancing BSTs
Implementation and rotations
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Red-Black Trees
Properties, insertion, and deletion
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Assignment: Tree Implementation
Implement and compare different tree structures
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Graph Representations
Adjacency matrices, adjacency lists, and edge lists
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Depth-First and Breadth-First Search
Implementation and applications
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Shortest Path Algorithms
Dijkstra's and Bellman-Ford algorithms
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Minimum Spanning Trees
Kruskal's and Prim's algorithms
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Project: Pathfinding Visualizer
Build a web-based tool to visualize graph algorithms
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Hash Functions and Collision Resolution
Advanced hashing techniques
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Open Addressing vs. Chaining
Performance analysis and implementation
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Consistent Hashing
Applications in distributed systems
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