AI Engineer
Instructor-led bootcamp

Build the AI engineering skills companies actually need:
100+ hours of practice with live consultations, weekly portfolio-ready AI projects and code reviews
join now
NeXT launch: March, 23
IN partnership with
Jetbrains

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Our students work at

What it means to be an AI Engineer?

Architect and implement LLM pipelines and agent workflows
Design AI systems that integrate external tools and data via MCP
Implement and optimize RAG architectures with vector databases
Conduct monitoring, evaluation, security and cost control for LLM apps
Own deployment and infrastructure for AI systems (Docker, AWS, CI/CD)
Build portfolio projects proving you can ship AI products
Enter a market where 50%+ of AI Engineer roles remain unfilled
20-35% salary premium over backend developers (2025 data)

Build systems around LLMs, not just interact with them

Intensive practice-oriented training
> 6 sprints including 6 real production use cases

> Focus on engineering skills (not academic theory, not research)

> Mentorship and code review from practitioners

>  3-4 GitHub projects you can show in job interviews & professional certificate
Build reliable
multi-agent systems
> Real production stack (LangChain, Cohere, Qdrant)

> Create robust pipelines using LLM APIs

> Automate any operations with complex AI agentic systems

> Experiment with different embedding models and providers
Ship AI
to production
> All metrics and monitoring done hands-on (Langfuse, Ragas)

> Implement guardrails and cost controls for LLM applications

> Deploy LLM apps with real-world tooling

Perfect for developers and tech managers who are

> Stuck between jobs or job hunting
> Ready to build their own products
> Currently employed and want to level up
> Eager to secure their position on the career ladder

Watch a free webinar to find out if this bootcamp is for you

What is an AI Engineer and why does the market need one?

> What's happening in the AI job market and why companies need applied engineers
> What an AI Engineer actually is and what it's not from a market lens
>  Why this transition makes sense for career transitioners and middle+ developers

Partnering with the best

> Creators of most popular professional dev tools
> Trusted by 11.4m developers worldwide
> Engineers at Tesla, X, Google, Visa, and Valve rely on JetBrains tools

Why Hyperskill Bootcamps work

Direct access to the instructor
Instructors who've built real products and explain complex concepts clearly will help you grow fast. You will have a direct access to an instructor during training, plus 1 week after bootcamp.
10-week structured curriculum
Learn AI building through practical sprints. Each sprint focuses on 1-2 hands-on projects that teach applied AI development step by step.
Built around industry needs
Curriculum adapted to current market goals (e.g., AI apps evaluation and monitoring).
Understand your skill growth
You'll reflect on the results of your skill improvements from module to module.
AI webinars from industry experts
Watch webinars and participate in live sessions where you'll learn to use the same tools that AI Engineers rely on to build more efficiently and effectively.
Stand-out portfolio projects
Build AI-based projects that reflect real industry tasks. Built on the same principles as programs at MIT or Y Combinator School: you build a project every week.

The team behind Hyperskill Bootcamps

I'm passionate about using AI to make learning smarter and more accessible. At Hyperskill, we're building the future of education, and I'm excited to be a part of it every day.
Nikolay Vyahhi
Founder, AI Educator, MIT Lecturer
I’ve built and deployed LLM systems at scale in production environments. This training teaches the exact mindset and tools I’d expect from my engineering team.
Ruslan Davletshin
Chief Technology
Officer
When designing this bootcamp, we kept asking ourselves what developers need to thrive in AI today and build confidence and momentum through real projects.
Alexander Patlukh
Chief Educator
I enjoy bridging the gap between complex technology and clear understanding. At Hyperskill Training, I help make advanced concepts accessible to learners.
Nikalina Ogorodova
AI/ML Engineer
I have over 7 years of experience in Data Science, Machine Learning, Deep Learning, and their applications, experienced in working on complex projects like the one we've built with Intel Labs. I'm happy to share my learnings with developers seeking innovative position on the market.
Ivan Rodin
AI Researcher
With 10+ years blending Software Engineering and UX Design skills and knowledge, I have experience of delivering user-centred products end-to-end. I leverage this integrated expertise to architect and build reliable and valuable AI Agents and LLM-powered apps.
Vladimir Kovtunovskiy
AI Product Engineer
and 10+ experienced educators specializing in technical training for developers

Bootcamp program

Introduction to LLMs
& Pipelines
sprint 1 (2 weeks)
> > Learn about an AI engineer’s role, typical tasks, and job requirements
> Understand the basics of LLMs and their current limitations
> Create automated analysis pipeline using MCP server to process and visualize real-time data
> Master prompting skills and basic prompting techniques while building LLM-based apps
‍

What students do:

Work with OpenAI API, write a CLI chat, build an assistant with retrieval, function calling and visualization.
Building Agents
& Multi-Agent Systems
sprint 2 (2 weeks)
> Explore the concept of AI agents
> Build autonomous systems using tools like FastAPI and LlamaIndex


What students do:

Build a FastAPI backend with multiple agents + GitHub PR Review Agent using LlamaIndex and GitHub Actions.
Vector Databases
sprint 3 (1 week)
> Learn to store and retrieve data for LLMs using Qdrant


What students do:

Build a FastAPI application on Qdrant: data loading, indexing, vector search, optimization.
Building RAG Systems
sprint 4 (2 weeks)
> Master LangChain to create Retrieval-Augmented Generation systems
> Build naive and advanced RAGs


What students do:
‍
Progress from vector search to RAG: build end-to-end pipeline, then implement query rewriting, reranking, HyDE, and data-source routing.
Monitoring & Security
sprint 5 (2 weeks)
> Monitor your app with Langfuse
> Learn to evaluate LLM-backed apps
> Apply best practices to keep your AI stack stable and secure
> Implement caching of chat history with Redis


What students do:
‍
Set up Langfuse and Ragas, collect metrics, track tokens, implement NeMo guardrails, cost-limits, and LLM-API proxy.
Deploying LLM-Based Apps
sprint 6 (1 week)
> Set up the full infrastructure to launch and run your AI projects in production


What students do:
‍
Package everything in Docker, deploy to AWS, manage environment variables and logs, demonstrate production version.

Curriculum that covers end-to-end AI systems lifecycle

Every project connects to a real business case, every module ships a measurable outcome
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What our learners say

We as developers need to be learning, learning, learning, and the current top topic is AI. So developers that want to move into this world – this bootcamp is the best choice.
Gabriel
Full Stack Developer
I like the material; it is a great chance to familiarize myself with AI tools. The proportion between Math and non-math tasks is just right. I also enjoy practical projects and exercises. Community helps with my questions and supports my motivation.
Avraham
Full Stack Developer
If I just needed a single project, I could hire a freelancer. But this is different. AI, especially LLMs, will be part of software development for a long time. <...>
You learn from people who’ve done it before, that’s what made studies meaningful.
Cezar
Chief Technical Officer
I feel confident and appreciate how AI Engineer program is structured: it gives truly practical knowledge. As someone project-oriented, I see this training as a way to fill my gaps, and I really admire what JetBrains and Hyperskill are building with their programs.
Lyubomir
Solo Entrepreneur
AI helps me be more productive at work and in life. Deep-dives into new concepts were fantastic, and I even created a project that could help JetBrains PMs make better decisions. Those who embrace AI will have a clear advantage moving forward.
Anastasiia
QA Lead, JetBrains
I highly recommend Hyperskill bootcamps because it’s fun, has a progressive approach, and is truly inclusive. No matter your personal situation, it gives you a fair chance to grow and succeed.
Michaela
Kotlin Developer Bootcamp
Hyperskill & JetBrains Academy platform provides effective learning with peer support, expert coaching, and AI-assisted code review. Their Java Backend Developer curriculum helps learners like myself understand coding concepts.
Ryan
Java Developer Bootcamp

Complete learning package for your 2026

10-week structured curriculum with expert guidance
1 year access to Hyperskill platform with 50+ courses
Bonus prep materials for comfortable learning pace
Live Discord community
Weekly recorded webinars
Live sessions with a dedicated instructor
Code reviews of projects you're building
Daily instructor support
Additional $100 off for you & your friend or colleague
+ one full year of Hyperskill Premium included
One-time payment + 7-day money back guarantee
3-payment plan possible
Additional price deduction for Hyperskill subscribers. Contact us for more details
$2499
$1999
Klarna installations possible for US residents. Please see this option in payment methods.
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Frequently asked questions

>
What if I already have Hyperskill premium subscription?

We're happy you're with us! We subtract the 4 months of Premium already included in the bootcamp. You get a discount on the bootcamp price up to $200 depending on your subscription plan. For exact numbers in your case, please contact our Educational Manager in WhatsApp, and we’ll calculate everything for you.

>
Can you help me request employer reimbursement for this bootcamp?

Absolutely. Reach out to our Educational Manager on WhatsApp, and we’ll share an offer PDF to help you present the bootcamp to your employer.

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Is it live or self-study?

Both. Live sessions every 1-2 weeks, daily async support, full materials and recordings available throughout and after the program.

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Do I get access to APIs and infrastructure?

Yes, we provide OpenAI tokens and credits via LiteLLM for the duration of the program. All deployment infrastructure works on free tiers (AWS, Qdrant Cloud, etc.).

>
What are the prerequisites to start this program?

You should be comfortable with programming and have some experience with Python. If you’ve used other languages but are new to Python, we’ll give you prep materials and 1-2 weeks of free access to Hyperskill to get ready. This bootcamp moves fast and covers technical topics, so it's best suited for people with any development experience.

If you’re unsure whether this bootcamp is a good fit for your background, feel free to contact our Educational Manager on WhatsApp, we'll be happy to help.

>
How long does it take to complete it?

We estimate that this program can be completed in about 10 weeks, plus 1 extra week for a break. We understand that each learner's pace may vary, however, most learners are expected to dedicate 8-10 hours per week to their studies.

>
What makes this different from other AI courses?

Unlike most courses, our program is highly practice-oriented and teaches how to build systems around them: backend, retrieval, monitoring, deployment. This is a fullstack AI engineering that is supported with real-life cases. Everything is done to upskill you to an AI engineer.

>
What’s the difference between the courses on Hyperskill and this bootcamp?

Behind this bootcamp there is a fast-paced, module-based program with new content. Unlike Hyperskill’s self-paced courses, it includes prerecorded webinars, live sessions, expert mentorship, career guidance and weekly coding sprints focused on building real AI products. You’ll get support, feedback and hands-on experience starting module 1.

>
Can I take a look at the program?

If you have any additional questions about the program, please reach out to us on WhatsApp or schedule a call with our educational manager.

>
What are my refund options?

You can request a full refund up until the end of the first week of studies. After that, a refund is impossible. For additional information and the refund schedule, please reach us in a chat or book a call for more details.

>
What’s included in instructor support?

Our instructors will conduct live sessions, assist you with project issues and complex topics, review your projects, and more. Your dedicated instructor will be available daily to answer your questions via a Discord channel and on live sessions.

>
Will I receive a certificate upon completion?

Yes, upon successful completion of this program, you will receive a certificate from Hyperskill. You will receive a certificate of completion for the program or a certificate of participance depending on your progress. You can easily add these certificates to your LinkedIn profile or show it to your employer to showcase your accomplishments.

>
How long does it take to acquire AI engineering skills?

Most learners build their core AI engineering foundation within the first 40 hours of focused practice (approximately 3 weeks at 10-12 hours per week).The full program runs for 10 weeks to ensure production-level depth and real-world project experience.

>
I don’t quite understand most of the terms you mention. For example, what are “reasoning loops” in AI agents?

That’s completely fine. Most developers don’t fully understand these concepts when they first encounter them. Terms like reasoning loops, RAG pipelines or multi-agent orchestration are part of modern AI system design, and they’re exactly what we break down step by step during the bootcamp. You’re not expected to know them now. Over the next 10 weeks (10-12 hours per week), you’ll implement them in real projects.

‍

>
Will this actually help me get hired?

We don’t guarantee job placement, but our graduates report that recruiters specifically ask about LLM-based projects. By the end of the bootcamp, you’ll have 3-4 GitHub repositories to share with recruiters hiring for AI Engineering roles — a solid, practical portfolio.

>
Do you share stories from your graduates?

Sure! You can read some of our graduates’ stories on the Hyperskill Blog page.