• 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 7: Vision and Perspectives

Vision

• Describe the structure of a convolutional neural network (CNN) and explain its use in image classification
• Describe the structure of the data provided as input to an image classifier in terms of batches and labels
• Explain the concept of transfer learning and how it is used in practice
• Identify some of the major milestones in the history of AI.
• Explain examples of social impacts of AI systems in wide use today
• Explain examples of biases in AI systems.

Contents