APPLIED AGENTIC AI

Artificial intelligence (AI) has entered a new era defined not just by what models can generate, but by what AI systems can autonomously do. Agentic AI, systems built on large language models (LLMs) that can reason, plan, use tools, access data, and act on behalf of users, is rapidly reshaping how organizations approach analytics, decision-making, and workflow automation. From AI agents that autonomously query databases and build dashboards, to multi-agent systems that coordinate complex analytical pipelines, agentic AI represents a significant shift in how analytics professionals design, build, and deliver insights.

This course provides a comprehensive, hands-on introduction to the design, development, and deployment of agentic AI systems for analytics use cases. Students will explore the foundational concepts behind LLM-based agents, including reasoning patterns (ReAct, Chain-of-Thought, Plan-and-Execute), tool use and function calling, memory architectures, and retrieval-augmented generation (RAG). The curriculum emphasizes practical agent development using modern frameworks such as LangGraph, LlamaIndex, CrewAI, and the OpenAI and Anthropic SDKs, and it addresses the ethical, governance, and safety considerations essential to responsible deployment.