Artificial Intelligence
Beginner
Prompt Engineering Fundamentals
Write clearer prompts and evaluate outputs with repeatable methods.
Course Overview
Learn task framing, examples, constraints, and structured outputs without relying on trial and error alone. Practical exercises show how to turn vague requests into testable behaviors.
What You Will Learn
Structure clear prompts with explicit role framing, context, and instruction boundaries
Implement zero-shot, few-shot, and chain-of-thought prompt techniques
Enforce structured JSON output generation using schema enforcement
Build automated prompt evaluation benchmarks to measure response consistency
Protect applications against prompt injection and adversarial input manipulation
Tools & Technologies Used
Prompt Workbench
Python
JSON Schema
Mesh API
Structured Curriculum
2 Modules · 6 Lessons · 100 Minutes Total
Module 1
Module 1: Prompt Construction & Reasoning Patterns
3 lessons
Module 1: Prompt Construction & Reasoning Patterns
Master prompt structure, framing, and multi-step reasoning techniques.
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Anatomy of an Effective System Prompt
Deconstruct role definitions, instructions, constraints, and delimiter formatting.
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Few-Shot Examples & In-Context Learning
Select and format representative input-output pairs to guide edge-case handling.
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Chain-of-Thought & Step-by-Step Reasoning
Prompt models to output intermediate reasoning steps before reaching final decisions.
Module 2
Module 2: Structured Outputs & Robustness Testing
3 lessons
Module 2: Structured Outputs & Robustness Testing
Generate machine-readable outputs and test against prompt attacks.
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Enforcing JSON Schema & Structured Outputs
Draft prompts that return strictly validated JSON structures for backend integration.
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Defending Against Prompt Injections
Identify indirect prompt injections and implement input sanitization boundaries.
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Building an Offline Prompt Evaluation Matrix
Benchmark prompt prompt performance across a test set of 20 realistic scenarios.
Practical Project & Capstone Outcome
🚀 Capstone Project
Structured Product Review Extraction System
Design, evaluate, and harden a system prompt that ingests customer reviews, extracts sentiment scores, identifies key product tags, and formats the output into strict JSON.
Prerequisites
- No prior coding required. Basic literacy with AI tools recommended.
Intended Audience
- Product Managers, Designers, and Content Strategists working with AI feature specs
- Software Developers standardizing system prompts in applications
Instructor Information
S
Sara Kim
Course Author & Industry Expert
Sara Kim is an AI Interaction Designer and Prompt Engineer who consults on user-centered LLM applications.
Frequently Asked Questions
Is prompt engineering still relevant with smarter models?
Yes! Clear task specification, output schemas, and security boundaries remain essential engineering requirements regardless of model capability.