CPSC 171 as a new course - Intro to AI Applications

We want to let you know that the department has added a new course for Fall 2024: CPSC 171, Introduction to AI Applications (https://courses.yale.edu/?srcdb=202403&subject=CPSC). It is intended for non-majors but we feel that some of you may find it an interesting read in the summer. Please see below for the textbook and syllabus. If you know of any non-CS majors who might have an interest in the area, please mention this class. As the field is evolving rapidly, if you have any insights or suggestions, please feel free to reach out to the instructor: Dr. Sue Chen (cc’d); they will be greatly appreciated.

Thanks and have a wonderful summer. Richard

==== Texbook: https://course.fast.ai/Resources/book.html Weekly Schedule Week 1: Introduction to Deep Learning

• Lecture 1a: Overview of Deep Learning (Chapter 1, Intro)
• Lecture 1b: Practical Deep Learning Applications (Chapter 2, Production) Week 2: Ethics and Data Handling
• Lecture 2a: Ethics in AI (Chapter 3, Ethics)
• Lecture 2b: Data Preparation and Cleaning (Chapter 4, MNIST Basics) Week 3: Deep Learning for Computer Vision I
• Lecture 3a: Image Recognition Basics (Chapter 5, Pet Breeds)
• Lecture 3b: Advanced Image Classification (Chapter 6, Multi-Category) Week 4: Deep Learning for Computer Vision II
• Lecture 4a: Image Augmentation Techniques (Chapter 7, Sizing and TTA)
• Lecture 4b: Introduction to Collaborative Filtering (Chapter 8, Collab) Week 5: Convolutional Neural Networks
• Lecture 5a: Understanding Convolutions (Chapter 13, Convolutions)
• Lecture 5b: Building ResNet from Scratch (Chapter 14, Resnet) Week 6: Tabular Data & Midterm
• and Embeddings Lecture 6a: 5a: Modeling Tabular Data (Chapter 9, Tabular)
• Midterm: covering material up to end of Deep Dive into NLP (Chapter 12, NLP Deep-Dive) Week 5 Week 7: Understanding Embeddings (Chapter 10, NLP) Week6:Natural Language Processing I
• Lecture 7a: Understanding Embeddings (Chapter 10, NLP)
• Lecture 7b: Basics of NLP (Chapter 11, Mid-Level API) Week 8: Natural Language Processing II
• Lecture 8a: Week8:Deep Dive into NLP (Chapter 12, NLP Deep-Dive)
• Guest Lecture Week 9: Advanced Architectures
• Lecture 9a: Architectural Details of Deep Networks (Chapter 15, Arch Details)
• Lecture 9b: Optimizers and Callbacks (Chapter 16, Optimizers and Callbacks) Week 10: Foundations of Deep Learning
• Lecture 10a: Deep Learning Foundations (Chapter 17, Foundations)
• Lecture 10b: Model Interpretation Techniques (Chapter 18, GradCAM) Week 11: Building Effective Models
• Lecture 11a: The Learner Class (Chapter 19, Learner)
• Lecture 11b: Conclusion and Future Directions (Chapter 20, Conclusion) Weeks 12: Frontiers in AI and Applications
• Lecture 12a: Topics in Generative AI
• Lecture 12b: AI innovations in Industry Week 13: Capstone Project
• This project is for students to apply what they’ve learned to a real-world problem related to their specific interests.