This is a hands-on workshop designed for anyone possessing basic programming skills and looking for how to apply those skills to the analytical practice of scoring and benchmarking. In this workshop, students will be exposed to two real-world data sets generated from the academic and healthcare sectors. Using these data sets, students will learn to design and implement scoring algorithms using Ruby, Python, R, or another programming language of choice.
This workshop consists of a lecture and a lab. The focus is on mastering the what, why and how of scoring and benchmarking. The lecutre will provide the what and why, the lab will provide the how.
Lecture: Data Understanding and Modeling
- Introduction to Analytics
- Benchmarking and Scoring Case Studies
- Data Understanding: Learn about the two sample data sets.
- Data Modeling: Apply descriptive analytics techniques to model the data
Lab: Applications in Scoring and Benchmarking
- Scoring Algorithms: Create scoring algorithms using sample data sets
- Benchmarking: Using computed scores, compare entities to see how they compare to eachother
- Sample Application: Build a single page web-application to visualize scoring and benchmarking
- Natural Language Score: TFIDF, ngrams, etc.
- Students should feel comfortable opening files and manipulating data using a programming lanuage (R, Python, Ruby, etc.)
- You will need to bring your own computer
This event will take place in a private office located in River North. RSVP for details.