Python for Data Science

Welcome to the repository for the course "Python for Data Science". This course is designed to introduce you to the world of data science using Python, one of the most popular languages for data analysis and machine learning.

Course Structure

The course is divided into three sessions, each focusing on different aspects of data science. The core material for each session is included in this repository.

Session 1: Brief intro to Python + tool set-up (VSCode w/ appropriate extensions, Miniconda)
- Overview of Python,
- Installing the software required,
- Inevitable debugging!
Session 2: Package and environment management + data analysis
- Introduction to package management,
- A brief look at virtual environments,
- A guide of basic data handling and analysis using Matplotlib & Pandas
- Reviewing Machine learning algorithms.
Session 3: Hands-on project + Azure ML Studio
- A deeper look into using data science packages,
- Overview of Azure ML Studio,
- Introduction to the capstone project.

Homework Notebooks

In addition to the core material, this repository also contains optional homework notebooks for self-led learning. These notebooks provide additional exercises and challenges to help reinforce what you've learned in the sessions.

Getting Started

To get started with the course, clone this repository to your local machine. You can then navigate to the session folders to access the course materials.

git clone https://github.com/ejones18/python-for-data-science.git
cd python-for-data-science

Prerequisites

This course assumes no prior knowledge and only requires access to a Windows device with internet connection.

Contributing