Prompt Engineering & Ai Ethics: Build Responsibly

Prompt Engineering & Ai Ethics: Build Responsibly
Published 7/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 1h 33m | Size: 294.37 MB​

Master advanced prompting techniques while learning to detect bias, protect privacy, and deploy AI responsibly
What you'll learn
Write reliable, reusable prompts using instructions, context, constraints, and few-shot examples
Apply chain-of-thought and step-by-step reasoning prompts to solve multi-part problems
Design role and persona prompts that enforce structured output (JSON, tables, schemas) your systems can trust
Debug a failing prompt systematically instead of guessing and retrying at random
Build multi-step prompt chains and retrieval-augmented prompts grounded in your own data
Identify where bias, hallucination, and privacy leakage actually enter a model's output
Apply fairness trade-offs and harm-mitigation techniques to real business AI systems
Build guardrails, red-team your own prompts, and document systems for audit and compliance
Navigate the global AI regulation landscape (EU AI Act, and emerging US and India rules) as a practitioner
Design human-in-the-loop patterns for high-stakes AI systems in hiring, lending, healthcare, and support
Build and defend a portfolio-ready capstone: an end-to-end ethical prompting system
Set up an ongoing AI ethics review process for a real team or product
Requirements
A computer with internet access and a free or ρáíd account on any major LLM (ᑕᕼᗩTGᑭT, Claude, or Gemini)
No prior AI or machine learning background required - we start from what a prompt actually is
Basic comfort using a web browser and copy-pasting text; no coding required (optional code examples included)
Description
This course contains the use of artificial intelligence.
AI is used to reframe the words, fixing spelling mistakes and grammatical mistakes and audio conversion.
Every prompt you write is also an ethical decision - and most courses teach the two as if they were unrelated. This one doesn't. You will learn to write prompts that actually work: instructions, context, constraints, few-shot examples, chain-of-thought reasoning, structured JSON output, and multi-step prompt chains grounded in your own data. And at every step, you will learn where things quietly go wrong - where bias enters a model's output, why hallucination is an ethical problem and not just a bug, how a careless prompt can leak private data, and what fairness trade-offs actually look like when you have to choose one. This course is for product managers and business analysts who need AI outputs they can trust, developers and technical writers who need consistent structured output, and compliance and risk professionals who need to understand how these systems actually fail. No machine learning background is required - we start from what a prompt actually controls, and build up from there.
You will work through real, worked scenarios: a hiring-screening prompt that quietly filtered out older candidates, a customer-support bot that hallucinated a refund policy that never existed, a healthcare triage prompt that performed differently across patient groups. Each one becomes a lesson in both technique and responsibility - how to build it right the first time, and how to catch it when it's wrong. By the end, you will have a portfolio-ready capstone - an end-to-end ethical prompting system, complete with guardrails, an audit trail, and a documented review process - and a working knowledge of the global regulatory landscape (the EU AI Act, and the emerging US and India frameworks) that increasingly governs this work. If you want to be the person your team trusts to ship AI features that don't blow up in production, this is the course that gets you there.
This course contains the use of artificial intelligence. AI is used to reframe the words, fixing spelling mistakes and grammatical mistakes and audio conversion.
Who this course is for
Product managers and business analysts who want to use AI tools reliably at work
Developers and technical writers who need prompts that produce consistent, structured output
Compliance, risk, and legal professionals who need to understand how AI systems can go wrong
Anyone preparing for a prompt engineering, AI ethics, or responsible-AI role
Team leads who need to set guardrails and a review process before deploying AI features

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