BCA Semester V - Data Mining
DATA MINING
Updated on Jun, 2025
Language - English
Development ,Data Science,Deep Learning
Lectures -84
Resources -8
Duration -13.5 hours
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Course Description
UNIT I
- INTRODUCTION : Introduction to Data Mining – Kind of Data – Functionalities – Interesting
- Patterns – Task Primitives – Issues In Data Mining - Data Preprocessing: Why Preprocessing
UNIT II
- ASSOCIATION RULES: Mining Frequent Patterns: Associations And Correlations - Basic
- Concepts – Frequent Item Set Mining Methods – Mining Various Kinds Of Association Rules
UNIT III
- CLASSIFICATION AND PREDICTION: Issues Regarding Classification and Prediction
- Decision Tree Induction Classification – Bayesian, Rule Based Classification – Support Vector Machine
UNIT IV
- CLUSTER ANALYSIS- What Is Cluster Analysis, Types Of Data In Cluster Analysis .
- Categorization Of Major Clustering Methods – Hierarchical Methods
UNIT V
- APPLICATIONS AND TRENDS IN DATA MINING: Applications and Trends in Data Mining:
- Data Mining Applications – Products And Research Prototypes – Additional Themes on Data Mining
- Social Impacts of Data Mining
Prerequisites
No Prior knowledge is Required.
Curriculum
Check out the detailed breakdown of what’s inside the course
Unit 1 Introduction
4 Lectures
-
Applications of Data Scraping
07:09
07:09
-
Introduction to Course, Scraping, Tools
01:39
01:39
-
Projects Overview
03:42
03:42
-
Why Data Scraping
02:42
02:42
Unit 2 ASSOCIATION RULES
5 Lectures
Unit 3 CLASSIFICATION AND PREDICTION
41 Lectures
Unit 4 Cluster Analysis
33 Lectures
Unit 5 APPLICATIONS AND TRENDS IN DATA MINING
1 Lectures
Instructor Details
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