Apr 22 - 24, 2025
Utility Analytics 202
Utility Analytics 202: Introduction to Forecasting in the Utilities
Continued population growth, socioeconomic improvements, and technological advancements in the past few decades have caused a significant rise in the consumption of energy and materials. Many utilities find themselves concerned — the volatility of wind and solar power generation, the uncertainty of rooftop solar adoption, and rising gas and electricity prices pose serious challenges. The modern consumer-centric paradigm of transactive energy has changed the traditional load forecasting methodologies, as it evolves and reshapes utility strategies.
This training intends to provide a comprehensive introduction to forecasting methods and present enough information about each method for participants to use them sensibly. Examples and applications from the utility industry, including forecasting with AMI data, are included.
Each Utility Analytics 202 training provides a Certificate of Participation and Completion and Continuing Education Units (CEUs) through the University of Oklahoma upon completion of the course. CEUs are awarded to training participants at a rate of one (1.0) CEU for every ten (10) contact hours of training. The Utility Analytics 202 public classroom course includes 18 hours of training (1.8 CEUs) and the virtual classroom course includes 12 hours of training (1.2 CEUs).
Course Calendar
New classes will be announced soon.
Earn a Certificate of Participation and Completion and Continuing Education Units (CEUs) from the University of Oklahoma.
Objectives
Upon completion of this training, students will be able to:
- Understand select applications of time series forecasting within the utility sector.
- Use statistical and graphical approaches to exploratory data analysis with time series data.
- Use software and/or programming languages (e.g., Python or R) to create statistical forecasts.
- Develop load, price, wind power, and/or solar power forecasts.
Who Should Attend?
- Analytics professionals who are interested in learning forecasting methods with applications in utilities.
- Utility professionals who find themselves doing forecasting without prior formal training.
- Utility Analytics 101 completers who want to continue advancing their analytics knowledge in the utility setting.
- Positions include, but are not limited to, Data Scientists, Forecasting Analysts, Energy Analysts, and Research Analysts.
Prerequesites
College- or university-level statistics and algebra or equivalent experience. Some exposure to statistical programming (for example, in Python or R language) is helpful but not required.
Pricing
Virtual Training
In-Person Training
Virtual Training
UAI Member
$
795
Early Bird Pricing*
-
Regular Pricing: $895
*Early Bird Pricing ends 5 weeks before the event date.
Non-Member
$
995
Early Bird Pricing*
-
Regular Pricing: $1095
*Early Bird Pricing ends 5 weeks before the event date.
In-Person Training
UAI Member
$
1695
Early Bird Pricing*
-
Regular Pricing: $1895
*Early Bird Pricing ends 5 weeks before the event date.
Non-Member
$
2095
Early Bird Pricing*
-
Regular Pricing: $2395
*Early Bird Pricing ends 5 weeks before the event date.
Not a UAI member and interested in learning more? Contact our Membership Team!
UAI Utility Membership is at the organizational level and is designed to aid utilities looking to realize desired business outcomes using analytics. Membership benefits are centered around an experience that allows utility members to share insights, knowledge and practical application techniques.
UAI Utility Membership allows everyone with a stake in analytics to take the lead, get involved and start their journey to become a smarter utility analytics professional.
James Wingate
Membership Development Manager
jwingate@endeavorb2b.com
404-226-3756
Meet The Instructors
Sridhar Radhakrishnan
Co-Director
OU Data Science and Analytics Institute
About OU DSAI
DSAI is an academic unit within the OU Gallogly College of Engineering. By partnering with OU DSAI to develop and deliver our Utility Analytics 101 course, we can better serve the need for workforce training in data science and analytics topics in the utilities sector across a broad spectrum of knowledge, awareness and expertise.
From Our Students
"I like that the Utility Analytics 202 course covered many different types of forecasting methods, including both theory and practical implementation. The instructor was engaging, friendly, and good at explaining difficult concepts in an understandable way. The case studies were helpful in making the students think about application of the concepts.”
"I loved learning a little about Python. Also the concept of machine learning was good stuff! This was one of the best classes I have taken. The hands-on exercises really helped the learning process for me.”
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