Intermediate

Aligning Generative AI with Business Cases

Evaluate and leverage generative AI, building agents with Semantic Kernel, plugins and RAG vector stores.

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8 sections

1 Table of Contents
2 Introduction
3 Module 1 — Evaluating and Leveraging Generative AI
4 Module 2 — Creating an Agent with Semantic Kernel and the OpenAI Chat Completions API
5 Module 3 — Extending Agentic Behavior with Plugins and Native Functions
6 Module 4 — Enhancing Agent Knowledge with RAG, InMemory Vector Store, OpenAI Embeddings and Semantic Kernel
7 Overall Course Architecture
8 Summary and Key Points

Use the OpenAI API end to end: GPT models, prompt engineering, practical apps and building your own chatbot.

Hands-on LLM use cases — sentiment analysis, summarization, fine-tuning, RAG and building AI agents.

Use AI tools for exploratory data analysis, analysis and generating polished analytical reports.

Evaluate open-source LLMs for performance, usability, licensing and practical deployment constraints.

Select deployment strategies, configure the technical environment and optimize open-source LLMs for production.

Integrate LLMs with the OpenAI Agents SDK, RAG, vector stores, moderation and session history.