AIDA.2203L Introduction to Machine Learning Lab
Id: 042958 Credits: 1-1Description
This is the lab class for AIDA.2203 Introduction to Machine Learning. The co-requisite lab provides hands-on implementation experience aligned with weekly lecture topics. Through eight structured programming labs, students work with real datasets using Python libraries such a NumPy, pandas, scikit-learn, and high-level neural network APIs. Labs cover supervised learning, classification, validation and model comparison, feature engineering, unsupervised learning, neural networks, and responsible ML evaluation. Students progressively build practical skills in implementing, testing, and documenting reproducible machine learning experiments, forming the technical foundation for the final project. This class must be taken with AIDA.2203 Introduction to Machine Learning in the same semester.
Prerequisites
Co-req: AIDA.2203 Introduction to Machine Learning.
Course prerequisites/corequisites are determined by the faculty and approved by the curriculum committees. Students are required to fulfill these requirements prior to enrollment. For courses offered through online or GPS delivery, students are responsible for confirming with the instructor or department that all enrollment requirements have been satisfied before registering.