Course Description
This course is an introductory course on data analytics and its application in smart energy
systems. It covers three major topics: 1) Primary data analytics theory including classification, regression, principal component analysis, etc.; 2) Hands on data analytics experiences with NumPy, Pandas, Matplotlib, & Scikit-learn packages; and 3) Applications in smart energy systems (with a focus on buildings energy systems), in which comprehensive experiments with real building energy data will be included.
In this course, students will learn systematic knowledge on data analytics and Python. They will also gain solid hands-on experiences in using Python to analyze smart meter data in energy systems.
Intended Learning Outcomes
CILO-1: Apply knowledge of mathematics, science, and engineering appropriate to the degree discipline. [POs: a]
CILO-2: Identify, formulate and solve engineering problems. [POs: e]
CILO-3: Use the techniques, skills, and modern engineering tools necessary for engineering practice appropriate to the degree discipline. [POs: k]
CILO-4: Use the computer/IT tools relevant to the discipline along with an understanding of their processes and limitations. [POs: l]