Data drives the world. We live in a world surrounded by Excel spreadsheets, databases, reports, and a never ending source of data available on the internet. How do you handle this data? What language do you use? How do you clean it up? How do you visualize it? What relationships are there in the data? What can you predict from the data?

In this 6 week workshop, we will explore these questions and more using the modern tools of data scientists: Python, Jupyter, Pandas, Matplotlib, Seaborn, Sklearn, XGBoost, and SHAP.

Have you ever wanted to learn these tools? Have you wanted to apply them to your data, either at work or data you took a personal interest in? Well, now is your chance. Through a combination of inverted classes, books, video, cohort interaction, and labwork, you will be able to walk away from this class with a project that you could use for work or put in your portfolio.

Outline:

• Week 1 - Python getting started

• Week 2 - More Python (advanced features lambdas, comprehensions) and Pandas

• Week 3 - Advanced Pandas

• Week 4 - Visualization - Matplotlib and Seaborn

• Week 5 - Machine learning - Dimension reduction, clustering, and classification

• Week 6 - Sharing notebooks and presenting results

Weekly Routine

Please work through the current module each week. The expectation is that you will keep up with each week's materials so you are prepared to take on the following lesson. T

Here are some key days of the week: 

• Monday: Start reviewing media

• Midweek: Live session. Please go through the media and start on the assignment before so you can come with questions.

• Weekends: Weekends are a great time to catch up with the current week's work. It is also a chance to get a head start on the upcoming week's work.