Flagship enterprise AI course
Enterprise Agentic AI Engineering using Azure OpenAI, MCP and OpenAI Agents SDK
Help your senior developers, architects and AI teams move beyond chatbots into secure enterprise agents that call tools, use business data, request approvals, emit traces and operate with measurable guardrails.
What Your Team Will Be Able To Do
The course is built for implementation teams that need practical decisions, not generic AI awareness. Every module connects agent design to data access, control, evaluation and production readiness.
Design agent workflows
Translate business processes into agent workflows with tools, memory, approvals and human oversight where risk demands it.
Build with enterprise tools
Use Azure OpenAI, tool calling, MCP concepts, OpenAI Agents SDK patterns and enterprise data retrieval safely.
Operate with controls
Add tracing, evaluation, cost controls, guardrails, access boundaries and release review practices before rollout.
Course Modules
Agentic AI foundations
Agents vs chatbots, planning, tool use, memory, autonomy boundaries and workflow mapping.
Azure OpenAI and model choices
Model selection, structured outputs, grounded prompts, tool calling and enterprise usage patterns.
OpenAI Agents SDK
Agent definitions, orchestration, handoffs, approvals, tracing concepts and multi-step workflows.
MCP for enterprise integration
MCP clients and servers, tools, resources, prompts, security boundaries and integration decisions.
Agentic RAG
Retrieval, search tools, memory, citations, validation and enterprise knowledge grounding.
Security, evaluation and operations
Prompt injection, tool poisoning, authorization, auditability, agent evaluation, latency and cost.
Hands-On Capstone
Participants build an enterprise agent design that retrieves internal knowledge, calls a business API or tool, asks for approval when required, returns traceable output and includes security and evaluation checklists.
Deliverables included
- Reference architecture for agentic enterprise systems
- Agent workflow design template
- Lab code outline and tool integration pattern
- Security checklist for agent and MCP workflows
- Evaluation checklist for quality, cost and risk
Bring This Course To Your Engineering Team
Share your target audience, cloud stack, preferred dates and whether you want labs tailored around Azure OpenAI, Azure AI Foundry, internal APIs, MCP servers or agent security review.