AI313
Introduction to Machine Learning
Core undergraduate course covering supervised learning, model evaluation, classification, regression, and practical machine learning workflows.
Teaching
My teaching focuses on artificial intelligence, machine learning, deep learning, database systems, software architecture, and multimedia computing. I emphasize theoretical foundations, algorithmic thinking, system-level understanding, and project-based learning in both undergraduate and graduate courses.
Current / Recent
AI313
Core undergraduate course covering supervised learning, model evaluation, classification, regression, and practical machine learning workflows.
BIL553
Graduate-level treatment of relational design, relational algebra, normalization, query processing, storage, indexing, and database system internals.
BIL635
Graduate course on neural networks, CNNs, RNNs, transformers, representation learning, generative models, and deep learning project development.
Teaching Portfolio
Course codes and titles are listed as used during the corresponding teaching periods.
Student Support
Course-specific announcements, assignments, reports, project templates, and evaluation documents are shared through the university learning management system or course pages when available.
I also supervise graduation projects and graduate-level course projects in artificial intelligence, machine learning, deep learning, multimedia analysis, database systems, and software engineering.