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Turn Your Backend Team into AI Engineers in 12 Weeks
Train 5+ engineers for the cost of 1 senior AI hire Built by practitioners,
backed by JetBrains
Hyperskill Training vs. Hiring
Outcomes that matter for your team
Your Team Before
Your Team After
How your teammates upskill
- Expert in systems, APIs, databases
- Limited exposure to ML/AI
- Ready to expand skillset
- Building production AI systems
- Learning with expert guidance
- Shipping measurable projects
- Ships end-to-end AI features
- Thinks in business metrics
- Mentors team on AI best practices
Structured learning designed for working engineers
End-to-end AI system lifecycle — from data to deployment to monitoring
Module 1: LLMs & Pipelines
What you'll build:
LLM-powered code documentation system using LangChain
Key skills:
- Prompt engineering
- Pipeline design
- API integration
Evaluation focus:
Module 2: AI Agents
What you'll build:
Autonomous agent that reviews pull requests and suggests improvements
Key skills:
- Agent architecture
- Tool use
- Reasoning loops
Evaluation focus:
Module 3: Context Engineering
What you'll build:
Context-aware support agent with knowledge retrieval
Key skills:
- RAG patterns
- Vector databases
- Context windowing
Evaluation focus:
Module 4: Design Patterns
What you'll build:
Multi-agent testing framework with evaluation chains
Key skills:
- Agent orchestration
- Pattern libraries
- System design
Evaluation focus:
Module 5: Security & Privacy
What you'll build:
Secure AI pipeline with PII detection and filtering
Key skills:
- Data sanitization
- Access control
- Compliance frameworks
Evaluation focus:
Module 6: Evals & Monitoring
What you'll build:
Production monitoring dashboard with automated evaluation
Key skills:
- Metrics design
- Observability
- Performance tracking
Evaluation focus:
What teams build with this expertise: production use cases
How each sprint works
What your team gains
Calculate your ROI
Why Hyperskill Training works
Common questions
Engineering teams with Python/programming background who want to build AI features. No ML experience required. Ideal for teams of 5–20 developers who need to ship AI capabilities without hiring a dedicated ML team.
The bootcamp is designed for working engineers with 8–10 hours per week commitment. Live sessions are recorded, and you can complete coursework on your own schedule within each 2-week sprint.
We focus on modern AI tools including Python, LangChain, vector databases, and popular LLM APIs. You'll also use GitHub, Jupyter notebooks, and deployment platforms. All tools are industry-standard and production-ready.
Each module includes measurable outcomes: code quality metrics, deployment success, cost optimization benchmarks, and business impact KPIs. Your team will ship real AI features that are evaluated on production readiness.
Yes! We offer customized cohorts for larger teams (15+). We can align projects with your specific business use cases and integrate with your existing tech stack. Contact us for enterprise options.
The program is designed for varying skill levels. Prerequisites are basic programming knowledge—no AI/ML experience needed. Advanced developers will benefit from production best practices, while beginners get comprehensive foundations.
Full refund available within the first 2 weeks if you're not satisfied. After that, we offer pro-rated refunds on a case-by-case basis. Our goal is your team's success, not lock-in.