Ai Curriculum

The AI Curriculum Modules at Texas State University are an initiative by the Center for Analytics and Data Science (CADS), developed with funding from our NSF Expand AI grant. These modules are designed to enhance AI education across disciplines, offering introductory, foundational and domain specific content. Made available through TXST Canvas, they support students and faculty in building relevant AI skills, promoting interdisciplinary learning and advancing workforce development. By exploring potential integration of these modules into courses, CADS aims to broaden access to AI knowledge and foster an inclusive environment for AI literacy across the university community.

Introduction to NLP

This course presents a practical introduction to natural language processing. It presents a foundational understanding of how text can be analyzed with statistical models and the steps required to prepare text for computer analysis. The course covers tokenization, n-grams, document-feature matrix, and includes a hands-on application to sentiment classification using the Naïve Bayes algorithm.

Module B1

Introduction to PyTorch

This course offers foundational deep learning knowledge, covering key concepts, mathematical background, practical model training using PyTorch, and an overview of deep learning applications.

Module B2

Introduction to Computer Vision

This course provides a comprehensive introduction to the fundamental concepts and techniques used in the field of computer vision. Students will explore how computers process and interpret visual data from the world, focusing on essential topics such as image processing, morphology, filtering, and edge detection.