Unit I — Foundations
01
Introduction and Course Hand-out Briefing
Understand course objectives, applications, and assessment methodology
Available
02
Foundations of Advanced Data Structures
Explain the need and applications of advanced data structures
Available
03
Amortized Analysis Techniques
Apply aggregate, accounting, and potential methods
Available
04
External Sorting and Memory Hierarchy
Understand external sorting and disk-based processing
Available
05
Tournament Trees, Buffering, and Run Generation
Explain tournament trees and optimal merge techniques
Available
06
Huffman Trees and Applications
Apply Huffman coding and tree construction methods
Coming soon
Unit II — Advanced Trees
07
Binary Search Trees Review and AVL Trees
Explain AVL properties and balancing operations
Coming soon
08
AVL Tree Rotations, Insertion, and Deletion
Implement AVL balancing operations efficiently
Coming soon
09
Red-Black Trees and Operations
Explain Red-Black properties and balancing rules
Coming soon
10
Splay Trees and Self-Adjusting Trees
Apply splaying operations and analyze efficiency
Coming soon
11
B-Trees and Variants
Explain B-Trees, B+ Trees, and B* Trees
Coming soon
12
Segment Trees and Interval Trees
Implement range and interval query operations
Coming soon
13
Tries and Digital Search Trees
Apply prefix searching and dictionary operations
Coming soon
14
Suffix Trees and String Processing Applications
Analyze pattern matching and text indexing methods
Coming soon
15
Comparative Analysis of Advanced Tree Structures
Compare balanced and indexing tree structures
Coming soon
Unit III — Heaps & Priority Queues
16
Binary Heaps and Heap Operations
Implement heap insertion, deletion, and heapify operations
Coming soon
17
Heap Sort and Priority Queue Applications
Apply heaps in sorting and scheduling problems
Coming soon
18
Binomial Heaps
Explain heap merging and binomial tree structures
Coming soon
19
Fibonacci Heaps and Amortized Efficiency
Analyze lazy operations and amortized complexity
Coming soon
20
Pairing Heaps and Double-Ended Priority Queues
Implement advanced heap and DEPQ operations
Coming soon
21
Comparative Study of Heap Structures
Compare Binary, Binomial, Fibonacci, and Pairing Heaps
Coming soon
Unit IV — Spatial Data Structures
22
Introduction to Spatial Data Structures
Explain multidimensional data representation techniques
Coming soon
23
k-d Trees and Multidimensional Searching
Implement multidimensional searching operations
Coming soon
24
Quad Trees and Oct Trees
Analyse spatial partitioning in 2D and 3D spaces
Coming soon
25
BSP Trees (Binary Space Partitioning Trees)
Explain partitioning techniques used in graphics and GIS
Coming soon
26
R-Trees and Spatial Indexing
Apply spatial indexing for GIS and database systems
Coming soon
27
Applications of Spatial Data Structures
Analyze applications in graphics, GIS, and machine learning
Coming soon
Unit V — Specialized Data Structures
28
Bloom Filters and Probabilistic Searching
Explain probabilistic membership testing methods
Coming soon
29
Priority Search Trees
Implement combined searching and priority operations
Coming soon
30
Persistent Data Structures
Analyze partial and full persistence concepts
Coming soon
31
Disjoint Set Union (Union-Find)
Implement union by rank and path compression
Coming soon
32
Applications of Specialized Data Structures
Analyze optimization and connectivity applications
Coming soon
Integration & Revision
33
Integrated Problem Solving on Tree Structures
Solve application-oriented problems on advanced trees
Coming soon
34
Integrated Problem Solving on Heaps and Spatial Structures
Solve problems on heaps and multidimensional indexing
Coming soon
35
Case Studies and Recent Applications
Discuss modern applications in databases, graphics, and AI
Coming soon
36
Revision and End-Term Preparation
Revise concepts and clarify doubts for examination
Coming soon