JetBrains

Hyperskill

AI Engineering Education by JetBrains & MIT alumni

Cohort 1

6-week bootcamp delivered through live webinars, interactive workshops, and focused practice.

AI Entrepreneur from Hyperskill

May AI Engineer

Bootcamp cuts through AI noise — from foundations to evaluating, securing, and deploying AI systems

June AI Engineer 

Learn to design, monitor, and deploy working AI systems. This transforms them to build robust, real-world LLM apps using prove

CEO Hyperskill | Lecturer JetBrains, MIT

Nikolay Vyahhi

I'm passionate about using AI to make learning smarter and more accessible.

CTO Hyperskill | Founder TheOna 

Ruslan Davletshin

I’ve built and deployed LLM systems at scale in production environments. 

AI, ML Engineer & Teaching Expert

Nikalina Ogorodova

I enjoy bridging the gap between complex technology and clear understanding.

AI Engineer & Researher

Ivan Rodin

I have over 7 years of experience in Data Science and Machine Learning.

Are you an experienced engineer looking to build systems on top of LLMs, not just experiment with AI tools out of the box?In 2026, working with AI increasingly means designing and shipping products powered by LLMs: assistants, RAG pipelines, agentic workflows, evaluation systems. Many engineers use these tools but far fewer know how to structure them into reliable, production-grade systems.This program focuses on that 2026 skillset.The Hyperskill AI Engineering Bootcamp is a 10-week, hands-on program for engineers who want to move to architecting reliable AI systems. You’ll build end-to-end projects using LLMs as components: designing retrieval pipelines, working with vector databases, implementing agents, setting up evals and handling deployment, monitoring and security.The emphasis is on practical system design, trade-offs and failure modes.Modules include: • LLM pipelines &amp; system design • Agents and multi-agent patterns • Vector search &amp; RAG systems • Evaluation, monitoring, security • Deployment of LLM-based applicationsExpect ~10 hours/week of focused work.

10-week Agentic  AI Engineering from experienced educators & practitioners

Design and build functional LLM pipelines end-to-end

Build AI agents with real autonomy using tools, memory, and function calling

Design high-quality context & RAG systems

Build advanced multi-agent & multimodal AI systems

Deploy secure and privacy-first LLM applications

Evaluate, test & monitor AI systems

Comfortable with programming know some Python. New to Python? We’ll give prep materials and 1–2 weeks of free Hyperskill access.

Basic programming experience (Python preferred)

On average learning takes 10–12 hours weekly completing hands-on tasks, projects, and practice at their own pace

Weekly time commitment (10-12 hours)

Live sessions are held in small groups with flexible timing and typically run twice

Availability for live sessions

Software engineers who want to level up from basic LLM usage to building production-ready AI systems, agents, and RAG pipelines

Technical PMs and team leads who want to raise their company’s AI capabilities and confidently drive adoption of modern AI systems

Developers looking to switch jobs by gaining the modern, in-demand AI engineering skills companies hire for today

Learn directly from Hyperskill

Hyperskill

Courses

Agentic AI Engineering 2026 Edition

Resources

AI Engineer Playbook: How Modern AI Systems Are Built

Workshop - AI Agents: Beyond the Hype