
Discover how AI agents act on behalf of users to achieve goals. From checking calendars to ordering cat food, they interact with tools and environments to perform tasks automatically.
Explore how large language models power generative ai by understanding and generating human language, enabling natural language processing (NLP), translation, summarization, and question answering.
Explain AI hallucination in which LLMs like ChatGPT generate false information as facts, why it happens (prediction over fact-checking, data gaps, ambiguous prompts), and how to mitigate with sources.
Discover retrieval augmented generation (rag) that uses a retriever with external data to reduce hallucinations, and explore embeddings, vector databases, and frameworks like lang chain and lama index.
Explore extracting information through prompt engineering and generative ai in a practical demo that highlights techniques for efficient data retrieval.
Set up an automated feedback response workflow in Zapier using Google AI Studio Gemini, mapping form inputs, and generating replies. Publish by connecting Gmail to deliver the crafted reply.
Explore ethics, governance, and compliance as the foundation of responsible artificial intelligence, guiding values, risk assessments, transparency, and diverse perspectives to ensure lawful, accountable, and scalable artificial intelligence.
This course contains the use of artificial intelligence.
Generative AI is transforming the way industries operate by enabling machines to produce human-like text, images, videos, code and other creative outputs that revolutionize communication, creativity, and decision-making. This course begins by tracing the fascinating evolution of AI, from traditional programming and neural networks to the rise of advanced generative models that power a diverse array of applications across fields like marketing, HR, and business strategy. You’ll gain foundational knowledge about what generative AI is and how it compares with traditional digital tools.
Central to this transformation is the skill of prompt engineering—the art of designing clear, effective instructions that guide AI models to deliver accurate, relevant, and innovative responses. You will learn how to create well-structured prompts, understand the impact of vague versus precise inputs, and master key prompting strategies including zero-shot, one-shot, and few-shot techniques. Building on these basics, the course dives deeper into prompt modifiers and model parameters such as tokens and temperature to help you fine-tune AI output for your specific goals.
Beyond individual models, you can explore the cutting-edge concept of AI agents—autonomous systems that combine generative AI with intelligent automation and decision-making to perform complex tasks and workflows.
By course completion, you’ll possess a comprehensive understanding of large language models (LLMs), prompt engineering workflows, and advanced prompting techniques like Chain of Thought and iterative approaches. Whether you are a product manager, developer, or strategist, this program equips you with the knowledge and hands-on skills to harness the full power of generative AI —empowering you to lead in the rapidly evolving AI landscape and unlock new possibilities across diverse applications.