Generative AI Foundations: Practical Skills for Today’s Workforce

Boost your team’s ability to think faster, work smarter, and uncover deeper insights by learning to harness Generative AI (GenAI). This hands-on course introduces the essential building blocks of GenAI, blending theory with practice so participants can immediately apply what they learn. From designing prompts that actually work to exploring real-world business scenarios, learners will walk away ready to integrate AI into daily workflows with confidence.

This course is designed for professionals in any field who want to explore the potential of Generative AI. Perfect for non-technical learners, project managers, business leaders, or anyone curious about applying AI responsibly in their work

Basic familiarity with using GenAI tools (e.g., ChatGPT, Copilot, or Gemini)

What You’ll Learn

By the end of the course, participants will be able to:

· Apply core GenAI concepts to everyday tasks and challenges.

· Explain how Large Language Models (LLMs) operate in plain language.

· Design prompts that drive automation, creativity, and problem-solving.

· Critically evaluate GenAI’s benefits, limitations, and risks.

· Improve productivity in writing, analysis, and decision-making.

· Apply the NIST AI Risk Management Framework to guide responsible use.

Module 1: Setting the Stage – Introduction to Generative AI

• Welcome and course objectives
• What intelligence means: natural vs. artificial
• How AI systems learn and generate outputs
• Generative AI explained: beyond automation to creation
• How LLMs actually “think”: tokenization, embeddings, prediction
• Multi-modal AI: text, images, and beyond
• Benefits, limitations, and common misconceptions

Module 2: Prompting with Purpose

• The art and science of prompt engineering
• Why wording matters: instructions, questions, and constraints
• Using personas and context for richer outputs
• Breaking down the anatomy of an effective prompt
• Practical strategies: layering, reflecting, adapting for different audiences
• Real-world examples: customer support, translation, data analysis
• Hands-on lab: Summarization, classification, and entity recognition

Module 3: From Concepts to Practice

• Case study: Building a customer service chatbot
• Exercise: Balancing concise vs. detailed outputs
• Prompting for creativity vs. accuracy
• Troubleshooting and refining GenAI responses

Module 4: Real-World Applications of GenAI

• Business use cases: marketing, compliance, knowledge management
• Industry impact: healthcare, finance, agriculture, education, and more
• Demonstration: Fraud detection, predictive maintenance, and climate modeling
• Discussion: Where AI shines—and where humans must lead

Module 5: Responsible AI and Ethics

• Why ethics is not optional in AI
• The NIST AI Risk Management Framework (AI RMF)
• Key trust factors: transparency, accountability, and fairness
• Global perspectives: EU AI Act, U.S. Blueprint for an AI Bill of Rights
• Identifying and mitigating risks in practical scenarios
• Reflection: Building an ethical AI mindset

Module 6: Bringing It All Together

• Key takeaways and strategies for workplace application
• Resources for continued learning
• Final hands-on challenge: Applying GenAI to a real-world scenario