Weekly Materials
Course slides, readings, and project resources by week
Course Schedule
Below are the weekly materials from our semester. Materials include presentation slides, activities and discussions, and related resources.
Weekly Breakdown
Weeks 1-2: Introduction to AI
Foundational concepts and course overview
- What is Artificial Intelligence?
- AI in the Media and Everyday Life
Weeks 3-4: Core AI Concepts
Machine learning, neural networks, and foundational technologies
- AI vs gen AI
- Machine Learnings
- Supervised vs. Unsupervised Learning
Weeks 5-6: Large Language Models
Understanding how modern AI text systems work
- Introduction to LLMs
- Hands-on with LM Studio
- Comparing Model Outputs
Weeks 7-8: Generative AI
AI that creates new content
- Text Generation
- Image Generation
- Ethical Considerations
Week 9: Data Center Visit
Physical infrastructure behind AI
- On-campus data center tour
- Hardware lifecycle discussions
- Environmental considerations
Weeks 10-11: Text Analysis Methods
Computational approaches to analyzing text
- Topic Modeling Introduction
- Latent Dirichlet Allocation (LDA)
- Working with ProQuest TDM
- Python/Jupyter Lab Setup
Week 12: Final Project
Comparative text analysis project
- Comparing TDM and Python LDA approaches
- Data preprocessing considerations
- Interpreting and presenting results
Accessing Materials
Course slides and materials are available through D2L or by contacting the instructor. The slides presentations and supplementary documents cover lecture content and in-class activities.
Note: If you're a researcher or student interested in replicating our text analysis methodology, please reach out for access to our project materials and code.