AI Engineering & LLM Application Development
Premier program for software developers transitioning into AI Engineering. Covers the entire modern LLM stack: embeddings, vector databases, robust RAG systems with reranking, multi-agent orchestration, tool integration via Model Context Protocol (MCP), and production observability.
(VAT included)
Total track tuition: €700 (VAT included)
Pay in 2 monthly installments of €350 (or €650 upfront payment)
Prices for individual enrollments include VAT. Corporate billing applies VAT according to current tax regulations.
Detailed Module Breakdown
Each module combines core engineering theory with practical hands-on exercises drawn directly from enterprise production codebases.
Module 1: AI Engineering Foundations & LLM APIs
- Modern AI application architecture: Tokens, Vector Embeddings, proprietary vs open-source models
- Direct API integration with OpenAI, Anthropic Claude, and Google Gemini APIs
- Real-time streaming responses, Structured Outputs (JSON Schema), and native function calling
Module 2: Production RAG (Retrieval-Augmented Generation) from Scratch
- The RAG ingestion pipeline: document loaders, text chunking strategies, and embedding models
- Production vector databases: deploying and querying Qdrant and Pinecone
- Semantic vector search versus hybrid search (dense embeddings + sparse BM25)
- Advanced RAG: Contextual Retrieval, Cross-Encoder Reranking, and Hypothetical Document Embeddings (HyDE)
Module 3: AI Orchestration Frameworks: LangChain & LlamaIndex
- Core concepts in LangChain and stateful graph orchestration with LangGraph
- Conversational memory management and persistent state persistence
- LlamaIndex for advanced indexing and structured data query routing
Module 4: Autonomous AI Agents & Model Context Protocol (MCP)
- Autonomous agent architectures: ReAct (Reasoning + Acting) loops and Plan-and-Solve patterns
- Advanced function calling and safe execution of external system tools
- The Model Context Protocol (MCP) standard: client-server architecture and tool integration
- Multi-agent orchestration and hierarchical task delegation
Module 5: Latency Optimization, Cost Reduction & Security
- Semantic caching with Redis / Momento to slash API billing by up to 60%
- Anthropic Prompt Caching and context window optimization
- LLM security defense: mitigating Prompt Injection, Jailbreaks, and proprietary IP leakage
Module 6: Observability, Evals & Production Deployment
- Distributed tracing, debugging, and continuous latency monitoring using LangSmith
- Building automated LLM evaluation test suites and accuracy benchmarks (Evals)
- Deploying full-stack AI applications on Vercel and Render with enterprise rate-limiting
Looking to deliver this curriculum internally for your technical team?
We can customize every module directly on your company's codebase or assign an independent senior trainer per diem (€600 – €1,500 / day).
What You Need to Know Before Starting
The syllabus is calibrated to ensure progressive, hands-on mastery:
- Intermediate programming proficiency (TypeScript / JavaScript or Python)
- Familiarity with REST APIs, databases, and the command line
- Laptop configured with a local development environment (Node.js or Python)
Everything Included in Your Enrollment
End-to-end learning, practitioner mentoring, and career placement support:
- Portfolio with 3 production-grade intelligent AI applications
- Mastery of high-demand technologies: LangChain, Qdrant, Pinecone, Claude API, MCP
- Preparation for high-paying AI Software Engineer roles
- Priority interview placement through SkillUp's IT Staffing network
Reserve your seat in the next cohort of AI Engineering & LLM Application Development
Cohorts are strictly limited to 12 participants to ensure 1-on-1 mentor guidance and line-by-line code review.