After this module, you will be able to explain how to customize prompts and be able to apply prompt engineering basics. You will be able to tell GenAI how to act and describe what the output you desire through prompt templates and frameworks. You will be able to explain the audience for the prompt receiver and train the AI to consider style in your prompting. You will also be able to use chain of thought prompting to add reasoning to your output and refine your GenAI output through iteration. Finally, you'll be able to implement prompt engineering frameworks.

After this module, you will be able to examine and discuss AI agent workflows and systems. You will be able to review the idea of building effective agents and identify that workflows are just mathematical algorithms. You'll be able to construct algorithms through workflows and defend the human in the loop. You will also be able to discover how AI uses other tools and finally build an Agentic workflow.

After this module, you will be able to define and describe multi-agent systems. You'll be able to explore characteristics of multi-agent networks. You'll be able to differentiate between types of feedback loops and consider how AI agents explore and exploit the landscape. You'll be able to recognize how emergent AI agents are agent-based models and create a multi-agent system.

After this module, you will be able to discuss common AI fears and critiques and consider how to use AI in spite of fears and critiques. You will be able to examine tasks that can be done by AI and explore rising opportunities and threats of using AI. You'll be able to consider practical recommendations of AI use and apply these recommendations to create a multi-agent system. Finally, you'll be able to reflect on agentic promises and perils.