Too Big to Excel: Energy Data Analytics
This three-day short course is for energy and policy professionals and all business professionals, regardless of industry, seeking an understanding of how to analyze and make sense of large datasets. Course content will include Python basics, using and utilizing Github, how to use Artificial Intelligence resources for developing code, geospatial analysis using Python and other energy data analytics topics.
Taught through a combination of lectures, discussion and hands-on practicums, students will understand how to use Python to analyze datasets and learn current practical engineering methods in relation to data analysis and coding with a focus on energy datasets.
Note: Students will be required to watch a short video before the course for instruction on configuring their computer with free downloadable software, including VS Code, Miniconda3 and GitHub. Additional self-study and practice examples are included with the course, along with answer sheets.
Dates:
TBD
Time:
10 a.m. – 12 p.m. CT
Location:
Online via Zoom
Price:
$600
- Understand coding basics.
- How to understand and write code confidently.
- How to visualize and collaborate code.
- Make more informed decisions on your own and/or better understand data analytic reporting.
- Achieving hands-on practice writing and implementing code.
Joshua D. Rhodes, Ph.D., is a research associate at UT Austin and a founding partner of IdeaSmiths, LLC, an energy consultancy. His current work focuses on smart grid and the bulk electricity system, including spatial system-level applications and impacts of energy efficiency, resource planning, distributed generation and storage. Rhodes is also interested in policy and the impacts that policy can have on the efficiency of the micro and macro economy. He is a regular contributor to “Forbes” and is an “AXIOS” Expert Voice. Rhodes sits on the board of the Texas Solar Energy Society and the data advisory board of Pecan Street Inc., a smart energy consortium. He holds a Bachelor’s in Mathematics and Bachelor’s in Economics from Stephen F. Austin State University, an M.S. in Computational Mathematics from Texas A&M University, and an M.S. in Architectural Engineering and Ph.D. in Civil Engineering from UT Austin. Follow Joshua on social media @joshdr83.
- Energy professionals.
- Reporters.
- Environmental advocates.
- Anyone interested learning data visualization quickly.
Participants will be awarded 0.6 CEUs upon completion of course as well as a Cockrell School of Engineering Digital Badge.
“I came into this class with a very limited background in coding and left with fundamental knowledge and confidence to code every day in my work with data.”
– Drew Kassel, UT Austin
“A great overview of prominent coding strategies and languages for data management and analysis. Students learn best open source (free) resources and how to use them, as well as a showcase of projects.”
– Michael Skiles, UT Austin
For questions and inquiries, please contact epd@engr.utexas.edu.