This repository contains all the course materials (except for datasets that can be downloaded from Kaggle.com) for the data science course of the Diploma in Banking Supervision at CEMFI.
This course serves as an introduction to machine learning techniques used in data science. While we will cover some of the underlying theory to get a better understanding of the methods we are going to use, the emphasis will be on practical implementation. Throughout the course, we will be using the programming language Python, which is the dominant programming language in this field.
The course is divided into two parts. In the first part, we will get a brief overview of the field, cover some basic concepts of machine learning and have a look at some of the most commonly used methods. In the second part, we will apply these methods to real-world problems, which hopefully will give you a starting point for your own projects. The course outline is as follows:
Part I: Overview and Methods
- Introduction to Machine Learning
- Basic Concepts
- Decision Trees
- Neural Networks
- Additional Methods
Part II: Applications
- Loan Default Prediction
- House Price Prediction
The course material is also available on https://datascience.joelmarbet.com.