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).
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Day 1
Brief Machine Learning Overview; Preparing for Machine Learning; Hands-on Application
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Day 2
Supervised Learning; Assessing & Improving Performance; Learning Algorithm Selection; Hands-On Application
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Day 3
Advanced Methods; Challenges in Machine Learning; Ethical Concerns and Identifying Biases; Unsupervised Methods; Time Series Modeling; Hands-on Application
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.
Pricing
Virtual Training
In-Person Training
Virtual Training
UAI Member
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Regular Pricing: $895
Non-Member
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Regular Pricing: $1095
In-Person Training
UAI Member
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Regular Pricing: $1895
Non-Member
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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 Instructors
Sridhar Radhakrishnan
Co-Director
OU Data Science and Analytics Institute
About OU DSAI
