Human–AI Collaboration and Workflow Automation
What this course is
Automation is easy to start and hard to trust. This course teaches you to build workflows where AI does the repetitive work and a person stays accountable for the outcome. You’ll connect language models, multi-modal tools and the productivity apps people already use, and streamline processes that actually exist.
Along the way you’ll learn task design, how to orchestrate several agents, how retrieval-augmented generation keeps answers grounded in real documents, and how to evaluate a workflow with humans in the loop. The goal is automation that is ethical, reliable and equitable, for business, education and community settings.
Catalog description
Design and implementation of human–AI collaborative workflows and automation. Integrate LLMs, multi-modal tools and productivity applications to streamline real processes. Task design, agent orchestration, retrieval-augmented generation (RAG), human-in-the-loop evaluation. Ethical, reliable, equitable automation for business, education and community applications.
- Design human–AI collaborative workflows that integrate LLMs, multi-modal tools and productivity applications.
- Implement automation using task design, agent orchestration and retrieval-augmented generation.
- Evaluate automated workflows with human-in-the-loop methods for ethics, reliability and equity.
What you'll build
- 1An automated workflow with a human checkpointTake a real, repetitive process and automate it, with a person reviewing and approving at the step that matters.
- 2A retrieval-augmented assistantAn assistant that answers from a specific set of documents (RAG), so its answers are grounded in your material, not guesses.
- 3An orchestration and evaluation planSeveral agents and tools working in sequence, with a plan for measuring whether the result is reliable, fair and worth keeping.
Tools you'll use
No-code and low-code tools. The exact list is set by the instructor each term.