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Apr 06, 2026
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CS 469 - Introduction to Generative AI
Units: 3
Generative AI focuses on computational models that learn patterns from data to create new outputs, images, text, or audio. Students will explore foundational concepts, cutting-edge architectures, and real-world applications. Programming assignment PyTorch and TensorFlow.
Prerequisites: CS 301 with a grade C- or better
Possible Instructional Methods: On-ground, or Hybrid, or Online-Asynchronous, or Online-Synchronous.
Grading: A-F or CR/NC (student choice).
Course Typically Offered: Fall & Spring
Student Learning Outcomes - Upon successful completion of this course students will be able to:
- Author creative and robust programs in PyTorch and TensorFlow for Gen AI models;
- Utilize various heuristics such as GANs, AutoEncoders, LLMs, and Multimodals to solve complex problems;
- Develop the ability to create Gen AI models for image and text.
- Apply Gen AI models to real-world problems;
- Utilize the safety and social implications of an ethical Gen AI model
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