• Unit 1: Introduction
• Unit 2: Supervised Learning
• Unit 3: ML Fundamentals
• Unit 4: Neural Models
• Unit 5: Embeddings
• Unit 6: Generalization
• Unit 7: Vision and Perspectives
• 376 Unit 1: Introduction to Generative Modeling
• 376 Unit 2: Language Modeling
• 376 Unit 3: Architectures
• Neural Computation
• 376 Unit 4: Generation and Prompt Engineering
• ML Systems
• 376 Unit 5: Multimodal Models and Diffusion
• 376 Unit 6: Miscellaneous Topics
• Learning Machines
• Context and Implications
• Review

Unit 1: Introduction

Introduction

• Describe the goals of artificial intelligence and machine learning.
• Describe the overall approach of how learning-based AI learns from data, in contrast with rule-based (symbolic) AI
• Contrast supervised learning, unsupervised/self-supervised learning, and reinforcement learning
• Write and execute basic Python code for numerical operations using Jupyter Notebooks

Contents