Training Catalogue / Applied AI Engineering

Prompt Engineering

4 modules
5 sessions

Modules

Take single modules or the whole track. Two hour sessions, combined into half days where it suits your calendar.

Foundation · 1 session

How LLMs Work for Builders

The mental model developers need: capabilities, context windows and model choice.

  • Model capabilities and hard limitations
  • Context windows and what fits in them
  • Choosing the right model for a task
  • Ethical and cost considerations up front
Foundation · 1 session

Core Prompting Techniques

Context engineering, structured prompts and the system-versus-user distinction.

  • Context engineering and structured prompting
  • System prompts versus user prompts
  • Using personas effectively
  • Specificity, output format and iteration
Practitioner · 2 sessions · multi-part

Advanced Prompting Strategies

Chain of thought, few-shot, self-criticism and prompt chaining for harder problems.

  • Chain of thought and decomposition
  • Zero-shot and few-shot patterns
  • Self-criticism and prompt chaining
  • Combining strategies for complex tasks
Practitioner · 1 session

Structured Outputs and Reliability

Get dependable JSON, Markdown and XML out of a model and manage hallucination.

  • Producing reliable JSON, Markdown and XML
  • Managing and reducing hallucinations
  • Domain-specific prompting patterns
  • Where prompting ends and real engineering begins

Enquire About This Training

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