AI & Machine Learning · Beginner → Expert
🤖 LLM Application Engineering
Engineer reliable LLM products with prompting, structured output, tools, retrieval, agents, evaluation, safety, observability, privacy, cost and production architecture.
Course roadmap
Pass each module exam to unlock the next module.
Module 1 · Beginner
LLM Foundations, Tokens, Context and Model Behavior
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Module 2 · Beginner
Prompt Design, Instructions and Few-Shot Patterns
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Module 3 · Beginner
Structured Outputs, Schemas and Validation
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Module 4 · Beginner
Tool Calling and Controlled Actions
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Module 5 · Intermediate
Embeddings, Retrieval and Vector Search
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Module 6 · Intermediate
RAG Ingestion, Chunking and Grounding
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Module 7 · Intermediate
Conversation State and Memory Architecture
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Module 8 · Intermediate
Agentic Workflows and Orchestration
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Module 9 · Advanced
Evaluation Sets, Rubrics and Regression Testing
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Module 10 · Advanced
Hallucination, Uncertainty and Verification
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Module 11 · Advanced
Prompt Injection and LLM Security
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Module 12 · Advanced
Privacy, Data Handling and Access Boundaries
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Module 13 · Advanced
Latency, Caching, Batching and Cost Control
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Module 14 · Expert
Observability, Tracing and Production Debugging
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Module 15 · Expert
Model Selection, Fallbacks and Reliability
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Module 16 · Expert
Human Review and Responsible AI Controls
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Module 17 · Expert
Expert Capstone: Production LLM Application
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Certification gate
Final course exam
Pass mark: 80%. Time limit: 360 minutes. All module exams must be passed first.
Locked until modules are passed