We will explore two key technologies—retrieval-augmented generation (RAG) and AI agents. Students will learn how to use these tools in their own work and appreciate the potential of these technologies on productivity and decision-making.

Learning Outcomes
At the conclusion of the course, you should be able to

• Implement basic RAG systems to enhance information retrieval and generation in workplace settings.
• Design simple AI agent workflows to automate tasks and support decision-making processes.
• Integrate generative AI tools with existing workplace systems to improve productivity.
• Evaluate potential applications of RAG and AI agents for specific business needs.
• Identify ethical considerations and best practices in applying generative AI technologies..

Topics Include

• Generative AI basics.
• The latest tools, using real-world examples.
• How RAG systems improve information retrieval and generation
• AI agent task automation, workflows, and how they support decision making
• Ethical Considerations
• Future Trends

Throughout the course, students will examine relevant case studies from various industries.

Skills Needed

Generative AI and LLM basics. Python for Machine Learning recommended but not required.