Utility Analytics 201

Utility Analytics 201: Applied Machine Learning for Utility Professionals

Today, widespread Machine Learning (ML) in the Utility industry has become more prevalent than imagined a few short years ago. This training introduces ML, including the concepts of exploratory data analysis, supervised learning (classification and regression), and unsupervised learning (dimensionality reduction and clustering). Participants will apply concepts through guided, hands-on activities.

UAI has partnered with the University of Oklahoma Data Science and Analytics Institute (OU DSAI) to develop and deliver Utility Analytics 201 training.

Utility Analytics 201 is delivered via public classroom, virtual classroom, and private group training throughout the year. All delivery formats consist of a lecture component and practical utility analytics application.

Each Utility Analytics 201 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 201 public classroom course includes 18 hours of training (1.8 CEUs) and the virtual classroom course includes 12 hours of training (1.2 CEUs).

Utility Analytics 201

Course Outline

Course Calendar

Earn a Certificate of Participation and Completion and Continuing Education Units (CEUs) from the University of Oklahoma.

Upon Completion of this Training, Participants will be able to:

  • Provide an overview of machine learning and related tools and topics.
  • Apply exploratory analysis, supervised learning, and unsupervised learning techniques towards industry use cases.
  • Be able to use predictive analytics methods to produce insights or solutions to a problem, given appropriate datasets and tools.
  • Understand how to evaluate and improve models and perform error detection/correction.

Who Should Attend?

  • Analytics professionals who are interested in machine learning methods with applications in utilities.

  • Utility Analytics 101 completers who want to continue advancing their in-depth knowledge of analytics in the utilities setting.

Why Attend?

UAI built this course with guidance from data science and analytics experts that are members of our Strategic Advisory Board and Executive Advisory Council. We’ve partnered with The University of Oklahoma Data Science and Analytics Institute (OU DSAI) to develop and deliver a training that delivers solid ROI and will help attendees stay ahead of the game.

Attendees will earn a Certificate of Participation and Completion and Continuing Education Units (CEUs) upon completion of the course.


Virtual Training

In-Person Training

Virtual Training

UAI Member

$ 795 Early Bird Pricing*
  • Regular Pricing: $895


$ 995 Early Bird Pricing*
  • Regular Pricing: $1095

In-Person Training

UAI Member

$ 1695 Early Bird Pricing*
  • Regular Pricing: $1895


$ 2095 Early Bird Pricing*
  • Regular Pricing: $2395

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

Meet The Instructors

Sridhar Radhakrishnan

OU Data Science and Analytics Institute


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