Module Materials
Explore our modules that can be helpful for building course materials.
| Title | Type of Material | Author | Institution |
|---|---|---|---|
| AI In Action Webinar | This two-part seminar explores real-world applications of AI across consumer-facing platforms, highlighting how intelligent models move beyond automation to deliver… | ||
| Casuality | This module is a lecture slide that explains casuality. | ||
| Casuality Homework | This module is a hands-on homework assignment that students can enhance their understanding of causality and develop programming skills via Google Colab. | ||
| Data Ethics Webinar | This webinar was designed to encourage students and faculty to stop and think about the ethical standards of data science. Ramón discusses three founding principles of data… | ||
| Intro to Neural Network | This module introduces neural networks, and how to design neural networks to solve problems like classification and prediction. | ||
| Linear Regression | This module contains a video lecture, notes, and a lab over Linear Regression. The correlation coefficient and “Line of Best Fit” are discussed. KNIME Analytics Platform… | ||
| Multiple Models, Explainability, and Bias | Students explore the space of good models and reflect on those that are more explainable and open to examination for interpretation by subject matter experts and for bias by… | ||
| Network Intrusion Detection with AI | This module provides data code to demonstrate how attacks can be detected in a packet capture file. | ||
| Principles of Graphical Integrity | Six general principles of graphical integrity |
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