DASC new courses

  

1. DASC 728/828, “Deep Learning Fundamentals and Applications” (Deep Learning Fund & App) (frank)
   “This course covers key components of deep learning framework, including loss functions, regularization, training and batch normalization. The course also covers several fundamental deep learning architectures such as multilayer perceptrons, convolutional neural network, recurrent neural network and transformers, as well as some advanced topics such as graph neural network and deep reinforcement learning. The class activities include traditional lectures, paper reading and presentation, and projects.”
   Prerequisites: be: CS 422 or CS 522 or CS 480 or CS 580 or CS 722 or CS 822 or CS 733 or CS 833 or CS 620, or other equivalent courses at the discretion of the instructor. 
2. DASC 605, “Statistical Inference and Experimental Design for Data Science” (Stat Inf & Exp Design for Data Sci) (Trent)
   “description”
   Prerequisites: STAT 603 and instructor approval
3. DASC 715/815 Generative AI (3 credits)
4. ·         Course Description: This course provides a deep dive into the foundations and current advancements in generative AI. It covers key concepts such as transformer models, GANs, VAEs, LLMs, and their applications across various fields, emphasizing both theory and hands-on learning, including ethical considerations such as fairness and bias mitigation. Students will develop a comprehensive understanding of generative AI and gain practical experience.
5. ·         Grading: Normal/Letter, Pass/Fail, Audit allowed.
6. ·         Prerequisite courses: Prior programming experience are expected.
7.  
8. DASC 717/817 AI for Health Sciences (3 credits)
9. ·         Course Description: This course explores the application of AI in health sciences, focusing on machine learning, NLP, computer vision, generative AI techniques for diagnostics, treatment planning, patient monitoring, and biomedical research. It covers precision medicine, ethical AI, and the integration of AI into practice. Students will gain a deep understanding and practical skills to develop innovative AI solutions that address real-world challenges in health sciences.
10. ·         Grading: Normal/Letter, Pass/Fail, Audit allowed.
11. ·         Prerequisite courses: Prior programming experience are expected.
12. DASC 7xx/8xx, “Data-Driven Computational Imaging” (Dushan)
    “please update course number, title and description after coordination with CS”
13. DASC 600 (Sampath)
    “please update title and description”
14. DASC 699  Thesis Research  (3 Credit Hours) 
    Prerequisites: Departmental permission required
15. DASC 697 Independent Study in Data Science  (1-3 Credit Hours)
    Independent study under the direction of an instructor.
    Prerequisites: permission of the instructor 
16. DASC 668 Internship (1-3 credits) (P/F only)
    Requirements will be established by the School of Data Science and Career Development Services and will vary with the amount of credit desired. Allows students an opportunity to gain a short duration career-related experience.

Actually submitted 

CS 781 AI for Health Science, 

Cross-listed and/orEquivalent Courses

CS 881, DASC 781, DASC 881

CS 782 Generative AI , cross listed with CS 882, DASC 782, DASC 882