AI Agents in Production
A 6-week intensive course.
Build agents that automate business workflows, deployed, monitored, and ready for production.
€1,500
Course Overview
Build, deploy, and scale autonomous AI agents in 6 weeks
Start Date
October 3, 2026
Duration
6 weeks
Format
Online · Post-work · 2 sessions per week
Investment
€1,500
- Language
- English / Portuguese
- Instructors
- 3 practitioners
- Payment
- Single payment
- Certificate
- Yes, upon completion
What you will ship
By the end of the course, you'll have done all of this, for real:
Deploy autonomous agents
In a container, served as a REST API, with monitoring and cost tracking.
Wire up real tools and APIs
Function calling, MCP, web search, code execution. Beyond the toy retriever.
Build memory and RAG
Short- and long-term memory, vector stores, and retrieval pipelines integrated into agents.
Design multi-agent systems
Supervisor patterns, agent handoffs, and pipelines for real business use cases.
Ship portfolio pieces
Demo Day, GitHub repo, LinkedIn write-up. Tangible proof of what you can do.
Track cost and scale
Parallel runs, retries, and cost-per-run tracking from day one.
Is this course for you?
Basic Python is required. Everything else below is recommended, not mandatory.
Recommended
- Comfortable writing 100+ lines of Python
- Have called an HTTP API from code
- Use Git daily
- Have an OpenAI or Anthropic API key (or willing to get one)
Not for you if
- You're a complete beginner to programming, start with the Advanced AI Solutions
- You want to learn how agents help you write code, pick Agentic Engineering
Curriculum. Six modules. Six weeks.
One agent in production.
Foundations of AI Agents
Agentic loops, ReAct, Plan-and-Execute, and the framework landscape. Learn when to reach for which tool, and why. Deliverable: a one-pager comparing two agent frameworks on a toy task.
Tool Use & Function Calling
Build your first end-to-end agent with function calling, MCP (consume third-party MCP servers and author one), web search, and code execution. Ship something you'd actually use. Deliverable: a working agent that consumes one third-party MCP server and exposes one tool of yours.
Memory & RAG for Agents
Short- and long-term memory, vector stores, and RAG pipelines integrated into agents, beyond the toy retriever. Deliverable: a RAG-backed agent with both short- and long-term memory.
Multi-Agent Systems
Supervisor patterns, agent handoffs, and multi-agent pipelines for real business use cases. Deliverable: a supervisor pattern across three sub-agents with handoffs.
Production Deployment & Observability
Container packaging, REST APIs, state management, monitoring, and cost-per-run tracking. The unglamorous half that matters. Deliverable: agent packaged in a container served as REST, with traces, golden-dataset evals, and cost-per-run.
Capstone, Agent at Scale
Build and deploy your final project. Demo Day with mentor feedback. Portfolio publication on GitHub and LinkedIn. Deliverable: deployed agent on a public URL, GitHub repo, and Demo Day video.
Meet Your Instructors
Learn from industry leaders and PhD holders with extensive real-world experience
Pricing
Exponential returns on a smart investment in your career.
Until 31 Jul
15 seats · 15 seats only
1 Aug – 27 Sep
Limited seats
From 28 Sep
Standard enrollment
DGERT-certified training entity: individuals can deduct 30% of the fee on their IRS, and for companies the hours count toward the mandatory 40 hours of annual employee training.
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Questions worth answering
Common questions about AI Agents in Production