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Three weeks of hands-on AI engineering training for developers who want to build, evaluate and deploy AI applications.f

Delivered by NVIDIA engineers in collaboration with YTU Startup House. Expect code, APIs, architecture decisions and working systems.

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Discover. Learn. Take Action.

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3 weeks

Training series: October 2026, delivered online

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800+ builders

Developers, software engineers, technical founders

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9 modules + Inspiration Day

Certificate of participation

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🧭 What this program is

This three-week bootcamp is for developers who want a more rigorous understanding of building AI applications and the engineering trade-offs behind reliable workflows that are shipped to production.

You will work through the components of a modern AI application: inference, prompting, retrieval, tool use, MCP, agent orchestration, evaluation, security and deployment. The program concludes with Inspiration Day, bringing together technical talks, keynotes and conversations with AI practitioners, founders, and investors.

This is an AI 201 program. You should already be comfortable writing code and have basic familiarity with LLMs. The focus is practical AI engineering.

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The program includes hands-on work with NVIDIA developer tools and hosted GPU resources to explore the path from prototype to deployment. Core engineering concepts (such as LLM API integration) are vendor-neutral and transferrable across your stack!

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📌 At a glance

Item Detail
Format Three-week AI Engineer Bootcamp led by NVIDIA's team + Inspiration Day (keynotes, technical sessions, networking)
Applications September 14-October 5 2026
Training series October 2026, 3 weeks Online (exact schedule TBC)
Inspiration Day November 2026 (December 2026 at the latest)
Training language English. All sessions, materials, code and Q&A.
Audience Developers, software engineers, technical founders
Prerequisite & level Ability to code, plus basic LLM/AI familiarity. Advanced beginner (AI 201, not 101)
Capacity 800+ participants
Certificate Certificate of participation for attendees
Curriculum Collaborator NVIDIA

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Application responses help the program team calibrate the depth and pace of the technical content. The aim is to keep the program appropriately challenging for engineers without assuming specialist ML experience.

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🛠️ The build path

flowchart LR
    A["Week 1<br>LLM internals, inference, prompting"] --> B["Week 2<br>RAG, tool calling and MCP"]
    B --> C["Week 3<br>Agents, evals, security, deployment"]
    C --> D["Inspiration Day<br>Keynotes and networking"]

📦 Curriculum: 9 modules