Part-time Data Science course

By Gianluca Campanella (g.campanella@estimand.com)

This repository contains teaching materials (slides and Jupyter Notebooks) for the part-time Data Science course at General Assembly London.

Aims

By the end of the course, you should be able to:

• Apply the Data Science workflow to solve problems with data
• Load, manipulate, and summarise data using pandas
• Produce basic data visualisations using matplotlib and seaborn
• Perform hypothesis testing, and interpret the output of generalised linear models
• Build and validate predictive models using sklearn

Schedule

Session	Topic
1	Introduction to Data Science
2	Managing data and analyses
3	Causality and study design
4	EDA and data visualisation
	Lightning talks
5	Statistical thinking
6	Generalised linear models
7	Time series
	Recap
8	Regression
9	Classification
10	Clustering
11	Dimensionality reduction
	Recap
12	Decision trees and random forests
13	Natural language processing
14	Ensemble methods
15	SVMs and neural networks
	Final presentations