GenAI and AI Application Engineering.
Build your next skill.

Format: 35 training days, live online. Foundation-to-project coverage with guided practice. Exact pace and batch schedule are agreed with the trainer.

Prerequisites: Basic Python, APIs and Git. This is an application-building course, not training a foundation model from scratch.

Days 1-5 | Python and LLM foundations

• Python refresh, HTTP/JSON, API clients and environment variables
• Tokens, context windows, embeddings and model selection
• Prompt design, structured outputs and responsible handling of data

Days 6-10 | Build an LLM application

• Build a chat interface backed by a model API
• Conversation state, streaming responses and error handling
• Latency, token usage and cost controls

Days 11-15 | Retrieval-augmented generation

• Document loading, chunking, metadata and embedding generation
• Vector search, hybrid retrieval and reranking concepts
• Build a grounded Q&A app with source citations

Days 16-20 | Evaluate and protect the application

• Create a small evaluation dataset and measure retrieval and answer quality
• Hallucinations, prompt injection, sensitive data and output validation
• Access-aware retrieval, adversarial tests and human review

Days 21-25 | Tools and agents

• Tool schemas, function calling and safe tool execution
• State, workflow routing, bounded agent loops and failure handling
• Approval gates for external actions and a small multi-step assistant

Days 26-30 | Deploy and observe

• Package the app, add tests and deploy a simple API
• Logging, traces, quality monitoring and prompt/model versioning
• Rate limits, caching and safe fallback behaviour

Days 31-35 | Capstone and interview practice

• Deliver a document assistant with citations, evaluation results and safe tool use
• Document architecture, cost assumptions and known limitations
• Code review, scenario questions and mock interview

Training and interview preparation

• Live online training with guided exercises and project discussion.
• Interview preparation, technical questions and mock interview practice.
• Live demo video available. Ask the team to arrange the demo and confirm the batch details.

This is a practical learning plan, not a promise of certification, a job or production-level expertise in 35 days. Cloud labs or model APIs may have usage costs; confirm lab access with the trainer before starting.