GenAI Foundations for Professionals

In this course, you’ll learn to use generative AI tools effectively and responsibly to boost productivity, creativity, and decision-making while ensuring accuracy, ethics, and data privacy.

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Course curriculum

1. Segment 00: Welcome & Course Introduction and Goals
2. Segment 01: Intro Video to Course
3. Segment 02: Module 1 Introduction
4. Segment 03: How Generative AI Works
5. Segment 04: Generative AI vs. Traditional Software
6. Segment 05: Everyday Examples of Generative AI at Work
1. Segment 06: What Generative AI Does Well
2. Segment 07: The Trade-Offs of Speed and Scale
3. Segment 08: Why Human Oversight Still Matters
1. Segment 09: Top 5 Myths About Generative AI
2. Segment 10: Separating Hype from Real Value
3. Segment 11: How to Spot Exaggerated Claims
1. Segment 12: How AI Adoption is Shaping the World
2. Segment 13: Industry Case Snapshots
3. Segment 14: Where AI Is Being Used Right Now
4. Segment 15 - Reading: What Are Large Language Models (LLMs): IBM
5. Segment 16 - Hands-On-Learning: AI vs. Search Engine Challenge: Understanding How Different Tools Support Thinking
6. Segment 17: Quiz: AI in Today’s Workplace
1. Segment 18: Module 2 - Introduction
2. Segment 19: Fundamentals of Clear Prompting
3. Segment 20: Common Prompting Mistakes to Avoid
4. Segment 21: Testing Your First Prompt
1. Segment 22: Role Prompting and Context Setting
2. Segment 23: Step-by-Step and Chain-of-Thought Prompts
3. Segment 24: Re-Prompting for Better Results
1. Segment 25: Brainstorming and Idea Generation
2. Segment 26: Summarizing and Structuring
3. Segment 27: Drafting Professional Documents with AI
1. Segment 30: Spotting Bias and Inaccuracy
2. Segment 29: Spotting AI Overconfidence
3. Segment 28: Knowing When to Step In Yourself
4. Segment 31 - Reading: Best Practices for Prompt Engineering with the OpenAI API
5. Segment 32 - Hands-On-Learning: Prompt Pattern Battle: Exploring How Prompt Structure Shapes AI Output
6. Segment 33 - Quiz: Troubleshooting AI Outputs
1. Segment 34: M3 - Introduction
2. Segment 35: Using AI for Reports_ Emails_ and Presentations
3. Segment 36: Streamlining Project and Task Management with AI
4. Segment 37: Productivity Gains and Pitfalls
1. Segment 38: Understanding Bias in AI Outputs
2. Segment 39: Why Hallucinations Happen (and How to Catch Them)
3. Segment 40: Establishing Checks for Accuracy
1. Segment 41: Using AI in Team Workflows
2. Segment 42: Transparency and Attribution
3. Segment 43: Building Trust When Teams Use AI Together
1. Segment 44: AI Adoption Success Stories
2. Segment 45: When AI Went Wrong Lessons from Failures
3. Segment 46: What These Cases Teach Us About
4. Segment 47 - Readings: The Beginner’s Guide to Hallucinations in Large Language Models
5. Segment 48 - Hands-On-Learning: AI Output Quality Control: Evaluating Risk, Bias, and Professional Judgment
6. Segment 49 - Quiz: Case Studies from Industry
1. Segment 50: M4 - Introduction
2. Segment 51: Privacy and Data Protection with AI
3. Segment 52: Fairness and Bias Awarenes
4. Segment 53: Accountability and Transparency
1. Segment 54: When to Use AI_ When Not To
2. Segment 55: Building a Personal “GoNo-Go” Checklist
3. Segment 56: Communicating AI Decisions Clearly
1. Segment 57: Mapping AI to Your Role and Goals
2. Segment 58: Integrating AI into Team Workflows
3. Segment 59: Staying Flexible as AI Tools Evolve
1. Segment 60: Key Trends in Generative AI
2. Segment 61: Skills Professionals Will Need in the Next 5 Years
3. Segment 62: How to Stay AI-Ready for the Future
4. Segment 63: - Reading: Responsible AI: From Principles to Practice
5. Segment 64: - Hands-On-Learning: Your Personal AI Decision Framework & 30-Day Roadmap
6. Segment 66: Outro Course Wrap-up Video
7. Segment 67 - Project: Personal AI Strategy & Responsible Adoption Plan
8. Segment 65 - Quiz: The Future of Work with AI

About this course

Free
68 lessons
4 hours of video content

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GenAI Foundations for Professionals

Course curriculum

Chapter 1: Generative AI Basics

Chapter 2: Strengths and Limitations of Generative AI

Chapter 3: Myths vs. Reality in Generative AI

Chapter 4: AI in Today’s Workplace

Chapter 5: The Art of Prompting

Chapter 6: Prompt Patterns

Chapter 7: Practical Applications

Chapter 8: Troubleshooting AI Outputs

Chapter 9: AI for Productivity

Chapter 9: Bias, Hallucinations, and Limits

Chapter 10: AI and Collaboration

Chapter 11: Case Studies from Industry

Chapter 12: Ethics and Guardrails

Chapter 13: Decision Frameworks

Chapter 14: Building Your AI Roadmap

Chapter 15: The Future of Work with AI

About this course

Discover your potential, starting today