Part-time Data Science course

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

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