AI-Powered Learning Platform

Subject Syllabus

CS-703 (B) - Data Mining and Warehousing

CSE · Semester 7

Course Modules

Learn topic-wise with Hyper AI and revise using mapped PYQs.

Introduction, Delivery Process, Data warehouse Architecture Data Preprocessing: Data cleaning, Data Integration and transformation, Data reduction Data warehouse Design: Datawarehouse schema, Partitioning strategy Data warehouse Implementation, Data Marts, Meta Data Example of a Multidimensional Data model Introduction to Pattern Warehousing

Basic concepts, OLAP queries, Types of OLAP servers, OLAP operations Data Warehouse Hardware and Operational Design: Security, Backup And Recovery

Data Types, Quality of data, Data Preprocessing Similarity measures, Summary statistics, Data distributions Basic data mining tasks Data Mining V/s knowledge discovery in databases Issues in Data mining Introduction to Fuzzy sets and fuzzy logic

Classification: Statistical-based algorithms Distance-based algorithms Decision tree-based algorithms Neural network-based algorithms Rule-based algorithms Probabilistic Classifiers

Hierarchical algorithms, Partitional algorithms Clustering large databases - BIRCH, DBSCAN, CURE algorithms Association rules: Parallel and distributed algorithms such as Apriori and FP growth algorithms