Module 1: Introduction to Generative AI (GenAI)

Objectives:

• Understand what Generative AI is

• Overview of how GenAI models work

• Key terminologies: LLMs, Tokens, Parameters, Fine-Tuning, Embeddings, etc.

Topics Covered:

• What is Generative AI?

• Difference between AI, ML, and GenAI

• Evolution of LLMs (GPT, BERT, Claude, Gemini, etc.)

• Types of GenAI applications (text, image, code, audio)

• Ethical considerations and risks

Activities:

• Icebreaker quiz: “GenAI Fact or Myth”

• Demo: ChatGPT generating a poem, image prompt with DALL·E

Module 2: ChatGPT Use Cases for Business and Productivity

Objectives:

• Explore practical use cases in various domains

• Understand the business impact of ChatGPT

Topics Covered:

• Role of ChatGPT in knowledge work

• Use cases: writing emails, summarizing documents, brainstorming ideas, customer support, coding assistance

• Industry-specific examples: marketing, HR, education, finance

Activities:

• Use Case Brainstorm: Participants map GenAI use cases in their role

• Hands-on: Use ChatGPT to draft an email, summarize a policy document

Module 3: Prompt Engineering Basics

Objectives:

• Learn how to write better prompts to get desired outputs

• Understand prompt structures, context, and constraints

Topics Covered:

• Anatomy of a prompt: instruction + context + output format

• Types of prompting: Zero-shot, few-shot, chain-of-thought

• Prompt tuning techniques

• Common mistakes and how to fix them

Activities:

• Hands-on: Refine prompts to improve output quality

• Group Exercise: “Fix the Prompt” game

Module 4: Using ChatGPT for Automation, Research, and Content Creation

Objectives:

• Leverage ChatGPT for everyday tasks

• Use AI as a co-pilot in research and creative workflows

Topics Covered:

• Automating repetitive tasks (checklists, reports, workflows)

• AI for ideation: storyboards, blog posts, LinkedIn content

• Research assistance: summarizing web content, compiling FAQs

• Productivity hacks: calendar planning, email drafts, meeting notes

Activities:

• Lab: Build a daily work assistant prompt pack

• Exercise: Use ChatGPT to generate content outlines and research summaries

Module 5: Exploring Tools like Microsoft Copilot, OpenAI Playground, and Others

Objectives:

• Introduce different tools and ecosystems powered by GenAI

• Learn to use Copilot and Playground for enhanced productivity

Topics Covered:

• Microsoft Copilot in Word, Excel, Teams, Outlook

• OpenAI Playground: UI walkthrough and settings

• Alternatives and integrations: Notion AI, Jasper, Canva AI, Zapier with AI

• Considerations for privacy and security

Activities:

• Hands-on with OpenAI Playground (custom instructions, temperature control)

• Demo: Microsoft Copilot generating a report in Excel and summary in Word

• Optional: Build a Zapier workflow using ChatGPT API

Wrap-Up & Reflection

Topics Covered:

• Key takeaways and action plan

• Challenges and responsible use reminders

• Q&A session

Module 1: What is Ethical AI?

Objectives:

• Define Ethical AI and its growing importance

• Understand the core values that drive ethical AI development

Topics Covered:

• Introduction to AI Ethics

• Principles of Ethical AI: Accountability, Responsibility, Fairness, Transparency

• Why ethics matters in AI today

• Challenges in aligning AI with human values

Activities:

• Group Poll: “Should AI have moral obligations?”

• Mini Exercise: Identify ethical concerns in a fictional AI product launch

Module 2: Bias, Fairness & Transparency in AI Models

Objectives:

• Identify sources and impacts of bias in AI

• Explore methods to measure and mitigate unfairness in models

Topics Covered:

• Types of Bias: Data, Algorithmic, Societal

• Fairness metrics and trade-offs

• Explainability and interpretability in AI systems

• Tools for transparency and accountability

Activities:

• Interactive Demo: Try an AI fairness tool (e.g., What-If Tool or Responsible AI dashboard)

• Group Discussion: “Can AI ever be truly neutral?”

Module 3: Governance & Compliance in AI

Objectives:

• Understand how organizations can manage AI risks through governance frameworks

• Learn about compliance standards and AI regulations

Topics Covered:

• AI Risk Management Frameworks

• Key regulations: EU AI Act, GDPR, NIST AI Risk Framework

• AI auditability and documentation

• Roles and responsibilities in AI governance

Activities:

• Case Analysis: AI compliance breach scenario

• Worksheet: Map your organization’s AI governance gaps (template provided)

Module 4: Microsoft’s and OpenAI’s Responsible AI Frameworks

Objectives:

• Learn how industry leaders embed ethics into AI development

• Explore responsible AI toolkits and documentation

Topics Covered:

• Microsoft Responsible AI Principles and governance approach

• OpenAI’s approach to alignment, safety, and human feedback

• Overview of tools: Microsoft Responsible AI dashboard, OpenAI moderation tools

• Best practices and implementation in real-world workflows

Activities:

• Tool Walkthrough: Responsible AI dashboard (Fairness, Explainability tabs)

• Reflection: How could you apply one principle in your team?

Module 5: Case Studies and Discussion

Objectives:

• Analyze real-world scenarios involving ethical challenges in AI

• Encourage critical thinking and team-based decision-making

Topics Covered:

• Case studies: AI recruitment bias, facial recognition issues, ChatGPT hallucinations

• Ethical dilemmas and conflicting priorities

• Organizational accountability and public trust

Activities:

• Case Study Breakout Rooms: Debate and propose ethical responses

• Wrap-up Group Discussion: “What does responsible AI look like in your world?”

Wrap-Up & Action Planning

Topics Covered:

• Key takeaways from the day

• Ethical AI checklist for your team/project

• Open Q&A and participant reflections

Module 1: Introduction to GPT Agents and Assistants

Objectives:

• Understand what GPT-powered agents are and how they work

• Explore the building blocks of AI assistants

Topics Covered:

• What is a GPT agent?

• Components: LLM, memory, instructions, actions (tools)

• Real-world agent examples (custom GPTs, personal assistants, AI bots)

• Difference between static prompts and dynamic agents

Activity:

• Walkthrough: Explore and interact with a few custom GPTs (e.g., Travel Advisor, Resume Helper)

Module 2: Creating a Simple Agent using OpenAI Tools

Objectives:

• Learn to create a basic custom GPT agent using OpenAI’s built-in tools

• Configure behavior, capabilities, and knowledge base

Topics Covered:

• Using ChatGPT’s “Custom GPT” feature

• Defining instructions, setting personality, uploading files, enabling tools

• Building an assistant without code

Activity:

• Hands-on Lab: Each participant creates a simple GPT (e.g., FAQ Bot or Onboarding Assistant)

Module 3: Using APIs and Automation (Python – Optional)

Objectives:

• Connect your GPT agent with external systems using APIs

• Explore automation with or without coding

Topics Covered:

• Calling ChatGPT via API (basic Python example with OpenAI SDK)

• Introduction to Power Automate for no-code integration

• Triggering workflows via email, forms, or database

• Example: Agent that summarizes form responses and emails them

Activities (Pick One Based on Audience):

• Tech-savvy group: Use Python to build a basic chat automation

• Non-tech group: Use Power Automate to connect ChatGPT with MS Forms and Outlook

Module 4: Agent Use Cases: Sales, Support, Scheduling

Objectives:

• Understand how agents can be applied in real-world workflows

• Brainstorm and design use cases for specific business needs

Topics Covered:

• Sales assistant: Lead qualification and product Q&A

• Support bot: Ticket triaging and knowledge base answers

• Scheduling bot: Calendar coordination and meeting setup

• Industry-specific ideas (education, healthcare, HR, etc.)

Activity:

• Group Exercise: Design a simple AI agent for a use case relevant to your team

Module 5: Demo and Q&A

Objectives:

• Share learnings, clarify doubts, and discuss enhancements

Topics Covered:

• Participant demos (optional volunteers)

• Common issues and how to improve your agents

Open Q&A on use cases, deployment, scaling