Program Overview:

Future Energy professionals have to gain deeper insights into operational data for making tougher decisions, especially as the industry navigates through its transition to a lower carbon footprint world. UH Energy’s new No Code Analytics and Machine Learning in Energy Program answers this need.

Designed and presented by leaders from industry and accomplished faculty from the University of Houston System, the program provides a series of micro-credentials or “badges” that will provide the necessary data sciences skillset to facilitate developing solutions to current and emerging challenges using advanced data-based decision making.

Credentialing Overview:

The course is offered in 15-hour modules, each over a 3 week period. Digital badges are awarded for each module. For completing each group of 3 Badges, learners will earn a Belt. There are three belts in the program. The Introductory Belt (Bronze) is followed by an Intermediate Belt (Silver) and finally by an Advanced (Gold) Belt. The Belts and Badges will be a permanent addition to your skillset and resume.

The first three badges, which together form the Bronze Belt in No Code Analytics and Machine Learning in Energy, are available online, starting June 5, 2023.

Schedule:

The Bronze Belt in No Code Analytics and Machine Learning in Energy starts on June 5, 2023. The Bronze Belt consists of three badges. Instruction for each badge consists of 6, 2.5-hour online sessions. Students should also allow 1.5 hrs. each for midterm and final test. Sessions are delivered two times per week, Monday and Wednesday, from 6:00pm-8:30pm, US Central Time.

• Badge 1: Data Processing & Machine Learning          June 5, 7, 12, 14, 19 and 21 
• Badge 2: Model Evaluation & Clustering                   June 26, 28; July 10, 12, 17, and 19
• Badge 3: Alternate Machine learning Algorithms        July 31; August 2, 7, 9, 14 and 16

Pricing (Student Discount):

Bronze Belt Bundle (Badges 1, 2 & 3): $125.00

Individual Badges: $50 per badge

Either: 

·       Rising senior, preferably in engineering, technology, natural sciences, mathematics or business, with an understanding of energy industry operations

·       Industry Professional