logo
Sign InSign Up
Certification Resources / Exam Outlines / Certified GPT Professional

Certified GPT Professional – Exam Outline

This exam outline defines the domains, objectives, and weighting for the Certified GPT Professional certification. This certification evaluates a candidate’s ability to use generative AI tools, understand prompt engineering, apply Python integration, and deploy practical AI solutions.

Exam Summary

  • Length: 75 minutes
  • Questions: 60 items
  • Passing Score: 71% or higher
  • Format: Multiple-choice

Domains & Weighting

Domain 1: Foundations of Generative AI and GPT Models (10%)

  • Identify the difference between traditional machine learning, deep learning, and generative AI.
  • Recognize how tokenization and embeddings are used to process language.
  • Explain the concept of transformer architecture at a high level (attention, context, sequence).
  • Differentiate between GPT model versions (e.g., GPT-3.5, GPT-4, GPT-4o) and their general capabilities.

Domain 2: Prompt Engineering and Output Control (20%)

  • Write clear, role-based prompts that define user, system, and assistant context.
  • Implement zero -shot, few -shot, and chain -of - thought prompting strategies.
  • Use delimiters, formatting, and constraints to control tone and output style.
  • Debug poor responses by identifying ambiguous or missing prompt instructions.
  • Apply JSON formatting or Markdown syntax in prompt design for structured output.
  • Utilize temperature, top-p, and max token parameters to adjust creativity or verbosity.

Domain 3: OpenAI Syntax and GPT Integration (40%)

  • Set up an OpenAI account and generate an API key.
  • Implement basic GPT API calls using Python (OpenAI or requests libraries).
  • Implement GPT API calls using JavaScript/Node.js (axios or fetch).
  • Use the /v1/chat/completions endpoint to create structured conversations.
  • Pass system and user roles correctly within API requests.
  • Parse and render JSON output from GPT API responses.
  • Handle and display GPT responses dynamically in a React (Vite) web interface.
  • Use environment variables to securely store and access API keys.
  • Implement API error handling (rate limits, invalid keys, token overflows).
  • Adjust temperature and max tokens in code to control creativity and output length.
  • Integrate GPT within N8N or Flowise nodes to automate tasks.
  • Connect GPT to external APIs (e.g., Google Search, email, or Notion integration).

Domain 4: Responsible AI, Security, and Compliance (15%)

  • Identify ethical concerns in AI-generated content (bias, misinformation, copyright).
  • Protect API keys and user data through environment variables or secret managers.
  • Understand and apply Responsible AI principles (fairness, accountability, transparency).
  • Describe privacy concerns when using user-generated prompts or proprietary data.
  • Apply content filtering or moderation APIs for safe GPT responses.
  • Recognize compliance standards like GDPR, FERPA, or COPPA in context.

Domain 5: Applied GPT Use Cases and Industry Solutions (15%)

  • Build a GPT-powered text summarizer or document assistant.
  • Create an AI chatbot that handles customer queries or support tickets.
  • Develop GPT-based automation workflows using N8N, Flowise, or Zapier.
  • Use GPT for educational tutoring, content writing, or research assistance.
  • Implement GPT for code completion or refactoring tasks.

Preparation Recommendations

Candidates are encouraged to study prompt engineering methods, explore Python-based AI integrations, and practice real-world GPT applications. Hands-on experience significantly increases exam success.