Riley is a software engineer in Austin, TX. He graduated with a degree in Marketing from Texas A&M University, which led to a job as a roofer. He quickly realized he needed a marketable skill and started selling websites to small businesses while simultaneously learning how to code. In 2008, he learned Ruby on Rails in order to turn his idea for a web app into a reality. ChubbyGrub was the result, and has been featured on LifeHacker, The Consumerist, and CNBC.com. Recently he made the transition to Data Science, finishing in the top 13% of the 2017 March Madness Kaggle Competition.
In recognition of his exemplary service in the classroom, Riley has been selected as a member of General Assembly's Distinguished Faculty program.
Data Science Immersive
Make smarter decisions by gaining the data analytics, data modeling, programming and statistics skills you need to start a career in data.
Introduction to Python Bootcamp
Learn to use Python as a powerful tool for analyzing and exploring data.
Python and Machine Learning Bootcamp Series
In this workshop series, you'll get a crash course on how to program with Python.
Introduction to Data Science and Machine Learning Bootcamp
This workshop will introduce students to data exploration and machine learning techniques.
Web Development Immersive
12-weeks. All day, every day. Learn the skills to become an entry-level web developer and the resources to get a job in this intensive program.
Dine + Dash: Pizza and Code for Beginners
This bootcamp will take absolute beginners through the basics of SQL to an ability to write queries with confidence.
Python Fundamentals Bootcamp
This workshop is for analysts, product managers, mathematicians, business managers or anyone else that wants to learn how to code in Python.
Talk Data to Me: Changing The Way Businesses Run & People Live
This monthly speaker series brings together industry experts to discuss how data is changing the way businesses run and people live.
Lunch and Learn: Intro to Data Science
This lunch and learn progam will define what data science is, review some of the main tools used by data scientists, and discuss how they can be implemented in real world work.