GuideIntermediate

Advanced Prompt Engineering Guide

Master the prompt engineering techniques that separate casual LLM users from production AI engineers: zero-shot and few-shot patterns, Chain-of-Thought reasoning, ReAct, Self-Consistency, prompt composition, systematic evaluation, and production prompt management with versioning, caching, and cost optimization.

64
lessons
8
modules
English · Spanish
available in
Yes
certificate
Free
access
NIEVA

Outcomes

What you'll be able to do

  • Design prompts systematically using structured frameworks, not intuition
  • Master zero-shot and few-shot prompting with example engineering and boundary testing
  • Obtain reliable structured outputs (JSON, Pydantic schemas) across multiple providers
  • Implement Chain-of-Thought reasoning with verification patterns for math, logic, and code
  • Apply ReAct (Reasoning + Acting), Self-Consistency, and Tree-of-Thought for complex tasks
  • Compose multi-stage prompt pipelines with chaining, decomposition, and context management
  • Evaluate prompts with quantitative metrics: LLM-as-judge, regression testing, A/B testing
  • Manage prompts in production: versioning, caching, cost optimization, monitoring, and deployment

Before you start

What you need to bring

It's for you if...

  • AI Engineers who use LLMs in production and need consistent, evaluable prompts
  • Python developers building applications with OpenAI/Anthropic who want to go beyond ad-hoc prompting
  • Backend engineers integrating LLMs into existing systems that require structured, reliable outputs
  • Engineers who completed LangChain & LangGraph and want to master the prompting layer
  • Anyone preparing for AI Engineering roles where prompt design is a core competency

Requirements and materials

  • Intermediate Python (functions, classes, basic async/await)
  • Experience calling LLM APIs (OpenAI, Anthropic, or similar)
  • Familiarity with REST APIs and JSON
  • At least one LLM API key (OpenAI recommended, Anthropic optional)
  • Python 3.11+ installed

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