Utility Analytics 301

Utility Analytics 301: Machine Learning and Big Data Analytics for Power Systems & Smart Grid

The course provides background information, real-world development experience, and in-depth discussions of big data analytics and machine learning in power systems and smart grid. The value, velocity, volume, and variety of big data in smart grid will be discussed. The basics of machine learning algorithms such as unsupervised learning, supervised learning, reinforcement learning algorithms, graphical learning, and generative models will be covered and taught. Important real-world applications of big data analytics and machine learning in transmission system, distribution system, and electricity market will be presented and discussed.

Utility Analytics 301

Course Outline

Utility Analytics 301: Machine Learning and Big Data Analytics for Power Systems & Smart Grid

Course Objectives

  • Understand how to assess the business value of machine learning and big data analytics in smart grid
  • Identify important machine learning and big data applications in smart grid
  • Explain and selection of machine learning algorithms
  • Learn about how to develop big data applications in smart grid
  • Understand how to apply machine learning algorithms to solve problems in transmission system, distribution system, and electricity market

Appropriate Audience

This course is appropriate for the following audiences:

  • Electric, combination utility, software provider, consulting company, proprietary trading firms, independent system operator.
  • Engineers, data analysts, data scientists, business analysts, and managers.
  • Distribution Planning, Distribution Engineering, Distribution Operators, Transmission Planning, Transmission Engineering, Transmission Operations, Customer Service.
  • Utility professionals who are interested in machine learning and big data analytics in power systems and smart grid
  • Utility Analytics 101 and 201 completers who want to continue advancing their in-depth knowledge of machine learning in power systems and smart grid

Prerequisites

  • College- or university-level statistics and algebra or equivalent experience.
  • Prior knowledge of machine learning and big data analytics is beneficial.
  • It is recommended, but not required, to complete the UAI Utility Analytics 101 and/or 201 course(s). 

Pricing

Virtual Training

In-Person Training

Virtual Training

UAI Member

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

Non-Member

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

In-Person Training

UAI Member

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

Non-Member

$ 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
jwingate@endeavorb2b.com
404-226-3756

Meet The Instructor

Nanpeng Yu

Dr. Nanpeng Yu

Associate Professor
University of California, Riverside

From Our Students