Monday, June 17, 2019 in Las Vegas
Full-day Workshop: 8:30am – 4:30pm
Practitioners who wish to learn how to execute on predictive analytics by way of the R language; anyone who wants “to turn ideas into software, quickly and faithfully.”
Knowledge Level: Either hands-on experience with predictive modeling (without R) or both hands-on familiarity with any programming language (other than R) and basic conceptual knowledge about predictive modeling is sufficient background and preparation to participate in this workshop.
The 2 1/2 hour “R Bootcamp” is recommended preparation for this workshop.
The instructor will guide attendees on hands-on execution with R, covering:
- A working knowledge of the R system
- The strengths and limitations of the R language
- Preparing data with R, including splitting, resampling and variable creation
- Developing predictive models with R, including the use of these machine learning methods: decision trees, ensemble methods, and others.
- Visualization: Exploratory Data Analysis (EDA), and tools that persuade
- Evaluating predictive models, including viewing lift curves, variable importance and avoiding overfitting
Hardware: Bring Your Own Laptop
Each workshop participant is required to bring their own laptop running Windows or OS X. The software used during this training program, R, is free and readily available for download.
Attendees receive an electronic copy of the course materials and related R code at the conclusion of the workshop.
- Workshop starts at 8:30am
- Morning Coffee Break at 10:30am – 11:00am
- Lunch provided at 12:30pm – 1:15pm
- Afternoon Coffee Break at 3:00pm – 3:30pm
- End of the Workshop: 4:30pm
Coffee breaks and lunch are included.
Brennan Lodge, Data Scientist VP, Goldman Sachs
Brennan is a self-proclaimed data nerd. He has been working in the financial industry for the past ten years and is striving to save the world with a little help from our machine friends.
He has held cyber security, data scientist, and leadership roles at JP Morgan Chase, the Federal Reserve Bank of New York, Bloomberg, and Goldman Sachs.
Brennan holds a Masters in Business Analytics from New York University and participates in the data science community with his non-profit pro-bono work at DataKind, and as a co-organizer for the NYU Data Science and Analytics Meetup.
Brennan is also an instructor at the New York Data Science Academy and teaches data science courses in R and Python.