Introduction to Data Mining for Business Intelligence

Engineering & Social Sciences Program
Madrid, Spain

Dates: 8/28/22 - 12/23/22

Engineering & Social Sciences

Introduction to Data Mining for Business Intelligence

Introduction to Data Mining for Business Intelligence Course Overview

OVERVIEW

CEA CAPA Partner Institution: Universidad Carlos III de Madrid
Location: Madrid, Spain
Primary Subject Area: Business
Instruction in: English
Course Code: 13478
Transcript Source: Partner Institution
Course Details: Level 300, 400
Recommended Semester Credits: 3
Contact Hours: 42
Prerequisites: This course assumes that the student knows the contents of Statistics I and Statistics II and the lesson of Properties of Matrices in Mathematics for Economics II. Some notions in Multivariate Statistics

DESCRIPTION

1. Learning the R Statistical Language.
1.1 Basic commands.
1.2 Graphics in R.
1.3 Statistical functions in R and basic programming.
2. Visualization Techniques for complex business data.
2.1 Principal component analysis theory.
2.2 Basic examples with R code.
2.3 Case studies.
3. Multidimensional Scaling.
3.1 Metric scaling theory.
3.2 Examples with R code.
3.3 Perceptual mappings in R.
4. Cluster Analysis.
4.1 Hierarchical methods.
4.2 Centroid methods: k-means.
4.3 Case studies.
5. Classification Trees.
5.1 Information theory.
5.2 Classification trees algorithms.
5.3 Real case: credit scoring.
6. Real Case Studies.
6.1 Comprehensive real cases involving all the studied techniques
8. Real Case Studies.
8.1 Comprehensive real cases involving all the studied techniques.


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