Program
AI for Business Professionals
19 lessons taking you from AI fundamentals to agentic workflows, responsible AI, and hands-on business case studies — taught live by Pavitra Gupta.
This syllabus will vary once we start the class. Feel free to give your input about what you want to learn and how you want to leverage it in the cohort.
Syllabus
Lesson 1 — Foundations
- What is AI, Machine Learning, Deep Learning, and Generative AI?
- Examples of each and how they are applied in the real world
- How they relate: AI vs. ML vs. DL vs. Gen AI
- Using AI to generate value, and cases of value creation
- Knowledge check
Lesson 2 — Machine Learning
- What is Machine Learning?
- Types of data used in ML, types of ML, and inferencing
- Use cases of ML
- Knowledge check
Lesson 3 — ML Development Cycle & MLOps
- Define problem, collect data, prepare data
- Build, evaluate, and deploy the model
- Monitor and improve: data drift, performance, system health
- The MLOps lifecycle: build → deploy → monitor → improve
- Knowledge check
Lesson 4 — Deep Learning
- What is Deep Learning?
- What are Neural Networks?
- Use cases of Neural Networks
- Knowledge check
Lesson 5 — Generative AI
- What is Generative AI?
- Foundational Models and LLMs
- Use cases of FMs and LLMs
- Knowledge check
Lesson 6 — Retrieval Augmented Generation
- What is RAG?
- Real-world applications of RAG
- Define use case → choose foundation model → improve performance → evaluate results → deploy application
- Knowledge check
Lesson 7 — Prompt Engineering
- What is a prompt?
- Major prompting techniques
- Prompt risks and misuses
- Knowledge check
Lesson 8 — Agentic AI
- What is Agentic AI and how does an AI agent work?
- Components of an AI agent
- Types and applications of AI agents
- Building and using an AI agent
- Knowledge check
Lesson 9 — Responsible AI
- What is Responsible AI, and what are the challenges?
- Considerations for selecting a responsible AI model
- Design considerations for developing responsible AI applications
Lesson 10 — Case Study 1
- Use of AI in making better decisions based on data
- Knowledge check
Lesson 11 — Case Study 2
- Business documentation
- Knowledge check
Lesson 12 — Case Study 3
- Customer support with Agentic AI
- Knowledge check
Lesson 13 — Comprehensive Guide to Claude AI
- Working end to end with Claude AI
- Knowledge check
Lesson 14 — Communication & Marketing
- Mastering communication with Claude AI
- Harnessing AI for marketing
- Applies equally to ChatGPT, Perplexity, and similar tools
- Knowledge check
Lesson 15 — Sales & Automation
- Mastering sales with Claude AI
- Automation
- Knowledge check
Lesson 16 — Workflow Use Case
- A full Claude AI workflow, start to finish
- Knowledge check
Lessons 17–19 — Summaries & Final Exam
- Summary 1
- Summary 2
- Final exam
