Generative AI is transforming how people create, communicate and work. This course offers a clear, non-technical introduction to tools such as ChatGPT and DALL·E, explaining how they work and why they matter. We explore everyday uses, limitations and ethical questions, helping participants understand the broader implications of the generative AI revolution. Suitable for beginners with no technical background.

DELIVERY MODE

• Face-to-Face

SUGGESTED READING

• Artificial Intelligence Basics: A Non-Technical Introduction, Tom Taulli
• Co-intelligence: Living and Working with AI, Ethan Mollick
• AI Superpowers: China, Silicon Valley and the New World Order, Kai-Fu Lee

COURSE OUTLINE

• Defining AI: AI is machines doing human tasks. Narrow AI (current reality) vs. General AI (future). Clarifying AI, Robotics, and Automation.
• ML Basics: AI learns from data, not explicit code. Analogy: "Cat vs. Dog" patterns. Types: Supervised (labeled) and Unsupervised (unlabeled).
• AI in Daily Life: NLP (Search/Spam), Recommendation Systems (Netflix), Computer Vision (Face ID), and Navigation Apps use AI algorithms.
• Generative Revolution: Generative AI creates new content. LLMs (ChatGPT/Claude) are next-word predictors. Image Generation (DALL-E) uses diffusion models.
• Future/Ethics: Trends: Multimodal AI & AI Democratization. Challenges: Reducing Hallucinations, Power Cost, and the goal of AGI.

LEARNING OUTCOMES

By the end of this course, students should be able to:

1. Define the difference between Narrow AI and General AI.
2. Explain the core process of Machine Learning, including Supervised and Unsupervised methods.
3. Identify and explain the AI technologies (NLP, Computer Vision) embedded in daily applications (Search, Face ID, Recommendations).
4. Describe the mechanics and limitations of Generative AI (ChatGPT, DALL-E) and the challenges of Hallucinations and Power Cost.
5. Discuss future trends like Multimodal AI and AI Democratization with confidence.