DATA ANALYSIS FOR BUSINESS

DATA ANALYSIS FOR BUSINESS

Kevyn Stefanelli

Instructional goals

Provide students with practical skills to work with and summarize datasets, aiming to provide business insights.

Intended learning outcomes

The students will have a great ability to use statistics to provide business insights. Also, the continuous assessment program will enhance the student's skills in Python.

Course Contents

Stats brief recap; Inference brief recap; Python brief recap; Regression models recap; Linear and Non Linear. regression models; Cluster Analysis; Principal Component Analysis; Basic of Machine Learning.

Reference Books

Course material.

Teaching Methods

Theory + Practical classes.

Assessment Method

Group continuous assessments (fortnightly frequency) + In class Group Continuous Assessment + Final Theory Exam (written in class)

Thesis assignment criteria

TBD

Week 1

Statistics and Inference Recap;

Week 2

Python recap; first assessment.

Week 3

Linear Regression Models

Week 4

Linear Regression Models

Week 5

Generalized Linear Regression Model.

Week 6

Generalized Linear Regression Model. Assessment

Week 7

Panel Regression

Week 8

Panel Regression Assessment

Week 9

Intro to Time Series

Week 10

Intro to Time Series

Week 11

Intro to Machine Learning

Week 12

Course Recap, Assessment