Prompt Engineer Learning Path

Practice defining roles, tasks, context, constraints, output formats, and evaluation criteria using a general-purpose AI assistant.

Build a structured foundation in prompting techniques and learn how to write, refine, and adapt prompts for practical generative AI tasks.

Create reusable prompt templates for several common tasks instead of relying on one-off prompts.

Test equivalent prompts with another AI assistant and compare instruction following, reasoning style, formatting, and response consistency.

Expand model comparison skills by testing prompt templates with another major AI assistant and documenting meaningful differences in results.

Develop practical prompt engineering skills through structured examples focused on using large language models in application and development workflows.

Confirm that you can create prompts with clear instructions, useful context, appropriate constraints, and defined output formats.

Practice writing research prompts that clearly define the question, scope, evidence requirements, and desired structure of the response.

Practice designing questions and synthesis prompts around a defined collection of source materials.

Extend prompt engineering skills beyond text-only workflows by exploring techniques for working with vision and multimodal AI models.

Extend prompt engineering practice to multimodal workflows by learning how prompts can combine and reason across different forms of input with Gemini.

Develop a repeatable method for comparing prompt versions and evaluating their outputs.

Create a multi-stage workflow in which prompts transform an initial input into a clearly defined final output through several controlled steps.

Create and document a complete prompt system that solves a clearly defined practical problem.

Review your portfolio project and verify that your prompt engineering process is systematic, testable, and documented.