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✨ AI Applied Engineering

Ship AI features inside real products: LLM APIs, agents, evals and production patterns.

⏱ 10 weeks Live Online β€’ Small batch

Overview

This course is for engineers who want to add AI capability to their existing products. You will build features that call LLMs safely, evaluate their output, and integrate into normal software workflows.

What you will learn

  • LLM API integration and prompt management
  • Retrieval-augmented generation
  • Tool use and lightweight agents
  • Evaluation and observability
  • Cost, latency and safety trade-offs
  • Shipping an AI feature end to end

βœ“ Job-Ready Track

This course is part of our job-ready track. It opens roles such as AI Engineer, LLM Application Developer, GenAI Engineer. Placement assistance and weekly interview preparation are included.

Outcomes depend on your effort, background and market conditions. We do not guarantee a job.

Tools & technologies

πŸ€–OpenAI / AnthropicπŸ”Pinecone🧩LangChain🐍Python⚑FastAPI🐳DockerπŸ“ŠLangSmithπŸ“ˆWeights & Biases

Syllabus

  • APIs, tokens and context windows
  • Prompt engineering for reliability
  • Structured outputs and parsing
  • Caching and cost control
  • Embeddings and chunking strategies
  • Vector databases
  • Retrieval evaluation
  • Building a document Q&A feature
  • Function calling
  • Multi-step reasoning
  • Error handling and retries
  • Building a research assistant
  • Golden datasets and metrics
  • Human-in-the-loop evaluation
  • Guardrails and moderation
  • Observability patterns
  • API design for AI features
  • Async processing
  • Container deployment
  • Monitoring and alerting
  • Feature scoping
  • Build week
  • Demo and review
  • Production checklist
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Have questions about this programme?

Book a free introductory call. We will discuss your background, the syllabus and whether this is the right starting point.

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