Overview

The Credit-Bearing Micro-Credential in AI for Intelligent Energy Systems is a 6-credit undergraduate micro credential that prepares students to apply AI data engineering methods to modern energy systems. The CBMC is intended for undergraduate students from computing, engineering, science, analytics, and related disciplines who have prior knowledge of introductory AI, Python programming, and basic statistics. It is especially suited to students interested in AI applications in sustainability, smart infrastructure, and energy analytics. The micro credential combines an existing major elective in AI Data Engineering with a newly developed course that explores AI applications in energy, including energy forecasting, smart buildings, anomaly detection, and intelligent energy decision support. The CBMC originates from the Bachelor of Science in Computer and AI Engineering and is proposed as a non-stackable micro credential. Admission Requirements Required prerequisites iclude: CENG 110 (or GEIT 113, ELEC 290, or equivalent) CSBP 110 (or CENG 230, or equivalent) STAT 210 (or equivalent) Equivalent courses are determined by the offering department Students are expected to have prior knowledge in: Introductory AI Programming Basic statistics Enrollment in the second course requires passing CENG 400 AI Data Engineering. Courses taken for the CBMC cannot be counted toward a student’s degree program. If overlap occurs, students must take alternative approved courses to fulfill degree requirements. Targeted Students The CBMC is intended for undergraduate students from computing, engineering, science, analytics, and related disciplines who have prior knowledge of introductory AI, Python programming, and basic statistics. It is especially suited to students interested in AI applications in sustainability, smart infrastructure, and energy analytics.