Week | Lecture Topic | Homework (datacamp.org) |
Module I: Understanding Artificial Intelligence |
1
8/31
| Course Introduction
- The instructor, the outline, classroom conduct, academic integrity, attendance, and grading policy.
What is Artificial Intelligence (AI)?
- Different Views and Approaches to AI
- AI vs ML vs DL
- AI in Industry
- AI in Enterprise
| Course: Understanding Artificial Intelligence
- Chapter 1 – What is Artificial Intelligence (AI)?
- Chapter 2- Tasks AI can solve
|
2
9/7
| The Power of AI and Its Human Side
- Ingredients to AI-driven organizations
- Best practices for AI democratization
| Course: Understanding Artificial Intelligence
- Chapter 3 – Harnessing AI in Organizations
- Chapter 4- The human side of AI
|
3
9/14
|
ChatGPT and Generative AI
- What can ChatGPT do?
- Enabling people to use GenAI
- Legal and ethical considerations
| Course: Introduction to ChatGPT
- Chapter 1 – Interacting with ChatGPT
- Chapter 2- Adopting ChatGPT
|
Module II: Intro to Machine Learning |
4
9/21
| EXAM I (Module I) Introduction to Supervised Learning | Course: Understanding Machine Learning
- Chapter 1 – What is Machine Learning?
- Chapter 2- Machine Learning Models
|
5
9/28
|
Introduction to Unsupervised Learning
| Course: Understanding Machine Learning
|
6
10/5
| Introduction to Deep Learning:
| Course: Understanding Machine Learning
|
Module III: Generative AI |
7
10/12
| EXAM II (Module II) Natural Language Processing | Course: Large Language Models (LLMs) Concepts - Chapter 1- Introduction to Large Language Models (LLM)
- Chapter 2 – Building Blocks of LLMs
|
8
10/19
| Transformers | Course: Large Language Models (LLMs) Concepts
- Chapter 3- Training Methodology and Techniques
- Chapter 4 – Concerns and Considerations
|
9
10/26
|
Neural Networks: Representation
- Non-linear Hypotheses
- Neurons and the Brain
- Model Representation
- Example and Intuition
- Multiclass Classification
| Course: Generative AI Concepts
- Chapter 1- Introduction to Generative AI
- Chapter 2-
Developing Generative AI Models
|
10
11/2
| Neural Networks: Learning
- Learning Cost Function
- Backpropagation Algorithm
- Backpropagation Intuition
| Course: Generative AI Concepts
- Chapter 1- Introduction to Generative AI
- Chapter 2-
Developing Generative AI Models
|
11
11/9
| Deep Reinforcement Learning
- Q-Learning
- Deep Reinforcement Learning
- Policies and Learning Algorithms
| Course: Generative AI Concepts
- Chapter 3- Using AI Models and Generated Content Responsibly
- Chapter 4-
Getting Ready for the Age of Generative AI
|
12 11/16 | Linear Classifiers in Python
- Applying Logistic Regression and SVM
- Loss function
| Course: AI Ethics
- Chapter 1- Approaching AI Ethics
|
13 11/23** | **No class. Happy Thanks Given!! |
PART IV: Disconnected Study |
14 11/30 |
EXAM IV (Module III)
Final Project
| TBD |
15 12/7 | Final Project | TBD |
16 12/14 | Final Exam and Final Project Presentation |