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Advanced LLM Integration in Production Applications

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A premium, complete course on advanced LLM integration in production applications, updated for 2026. Covers LLM API fundamentals (Anthropic, OpenAI, Google), integration architectures and patterns (Gateway, Queue-Based, Sidecar), streaming with SSE and Time to First Token, advanced error handling (exponential backoff, circuit breaker, graceful degradation), function calling and tool use (hands-on OpenAI and Anthropic implementations), multi-tool orchestration with the ReAct pattern, Model Context Protocol (MCP) — building and consuming custom servers, multi-model orchestration with intelligent routing (static, dynamic, cost-aware), multi-provider fallback and load balancing, cost optimization (model tiering, prompt caching, Batch API), productionization (exact and semantic caching, rate limiting, throttling, cost governance), full observability (structured logging, metrics, distributed tracing with OpenTelemetry, Langfuse, LLM-as-a-Judge), security (prompt injection, guardrails, output validation), compliance (GDPR, EU AI Act, consumer protection), 2026 advanced capabilities (extended thinking, reasoning models, structured outputs, multimodal vision and audio integration), plus complete hands-on projects.

9 modules
24 lessons
~26h duration
v1.0 version
AI professor An AI agent built into every lesson — ask questions and get instant answers based on the course content
Hands-on exercises Real scenarios and practical exercises directly on the platform, with instant feedback
Progress & analytics A personal dashboard with statistics, streaks, scores and structured learning paths
Interactive AI quizzes Questions generated by AI and adapted to your level, with detailed explanations
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What you will learn

Practical skills you gain by completing this course

Fundamentals of LLM Integration in 2026
Streaming and Error Handling
Function Calling and Tool Use
Model Context Protocol (MCP)
Multi-Model Orchestration and Optimization
Productionization
Security and Compliance
Advanced Capabilities for 2026
Final Quiz — Advanced LLM Integration

Who it is for

Developers Software engineers Solution architects CTOs / Tech Leads Data Scientists ML Engineers DevOps Engineers

Recommended level

Advanced

Assumes hands-on experience with AI and complex scenarios.

Updates

Regular

Content updated regularly with the latest practices from the industry.

Category

IT & Engineering

A technical course for IT professionals — available with individual course access or the IT Pro / All Access bundle.

Advanced level

Hands-on experience required

Assumes practical experience with AI. Covers complex scenarios and advanced strategies.

Always up to date

Up-to-date content

The course is updated regularly with the latest information, tools and practices from the industry.

Practical and applied

24 lessons with real examples

Each lesson includes practical scenarios, actionable checklists and quizzes to check your understanding.

Curriculum

9 modules, 24 lessons — structured to learn step by step.

9 modules
24 lessons
~26h of content
Interactive quizzes
Free preview available The LLM Landscape in 2026 — Models, Providers, and Ecosystem
Read the preview
1 Free preview lesson The LLM Landscape in 2026 — Models, Providers, and Ecosystem
Read the preview
2 Anatomy of an API Call — Request, Response, and Control Parameters
55 min
3 LLM Integration Architectures and Patterns
55 min
1 Streaming with SSE — Time to First Token and User Experience
55 min
2 Advanced Error Handling — Classification, Retry, and Circuit Breakers
55 min
1 Function Calling — From Text to Action
60 min
2 Practical Implementation: OpenAI and Anthropic
60 min
3 Multi-Tool Orchestration and the ReAct Pattern
55 min
1 MCP — The Universal Standard for LLM Integration
60 min
2 Building and Consuming MCP Servers
55 min
1 Model Routing Strategies in 2026
60 min
2 Fallback, Load Balancing, and Multi-Provider Resilience
55 min
3 Cost Optimization — Tiering, Prompt Caching, and the Batch API
60 min
1 Caching LLM Responses — Exact, Semantic, and Prompt Caching
55 min
2 Rate Limiting, Throttling, and Cost Governance
55 min
3 Observability — Logging, Metrics, and Distributed Tracing
60 min
1 Prompt Injection — Attacks, Defense, and Guardrails
55 min
2 GDPR, the EU AI Act, and Compliance for LLM Applications
50 min
1 Reasoning Models — Extended Thinking and Chain-of-Thought
55 min
2 Structured Outputs, Vision, and Multimodal Integration
55 min
3 Agentic AI: Building Autonomous Systems with LLMs
45 min
4 gpt-oss, DeepSeek V4, and Open-Source Models in Production
40 min
5 Official Resources, 2026 Updates, and Learning Paths
35 min
1 Final Assessment Test
25 min
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