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Responsible AI: Transparency & Ethics · LearnSpace
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Responsible AI: Transparency & Ethics

Курс от Coursera
Средний≈ 3.1 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Did you know that while 75% of business leaders agree AI ethics is important, most admit they lack the necessary tools or frameworks to implement it? According to Datamation, the majority of companies recognize the significance of AI ethics but struggle with practical implementation. The gap between knowing and doing is massive—and that’s where this course comes in. Responsible AI isn’t just about feeling ethical. It’s about building systems that are safer, smarter, and more transparent from the ground up This course is designed for professionals who are shaping the future of artificial intelligence. It’s ideal for data scientists, machine learning engineers, AI project managers, product leads, compliance officers, policy advisors, and ethics reviewers. Whether you're developing AI systems or ensuring they meet ethical and regulatory standards, this course equips you with the tools and knowledge to build responsible, unbiased AI applications. To get the most from this course, learners should have a basic understanding of machine learning workflows and the AI lifecycle. Familiarity with general technology concepts and the ability to prompt tools like ChatGPT will be helpful. While prior experience with Python or Jupyter Notebooks is beneficial, it’s not mandatory—this course is built to be accessible and practical. By the end of the course, learners will be able to identify and mitigate bias in AI systems, implement explainability tools like SHAP and LIME, and develop responsible AI checklists based on fairness and transparency. They will also learn to evaluate AI projects against compliance frameworks such as the NIST AI Risk Management Framework, ensuring that their systems are ethical, explainable, and aligned with industry standards.

Навыки, которые вы освоите

Responsible AIData EthicsArtificial IntelligenceGovernanceAI WorkflowsAuditingRisk Management FrameworkModel EvaluationMitigation

Программа курса

1 модулей · 21 учебных материалов

01Responsible AI: Transparency & Ethics21 материалов

Lesson 1: Auditing AI for Bias and Fairness

Welcome to the Course: Course OverviewЧтениеIntroduction and Welcome ВидеоUnderstanding AI Bias – Types and impact ВидеоSteps to Detect Algorithmic Bias Чтение

Учитесь у экспертов

Brian Newman

Founder & CEO | AI-Driven Consulting LLC

Starweaver

Global Leaders in Professional & Technology Education

Responsible AI: Transparency & Ethics
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в новой вкладке

Обучение на Coursera

≈ 3.1 ч

1 модулей

Язык: Английский

Субтитры: Арабский, Французский, Узбекский, Итальянский, Бразильский португальский, Корейский, Испанский, Японский, Казахский, Венгерский

Часть программы вашего университета
Bias in AI: How It Emerges in Development Видео
Using AI Fairness 360 Видео
Hands-On-Learning: Practical Bias Audit Challenge Взаимная проверка
Spotting and Fixing Bias in Your Models Обсуждение

Lesson 2: Making AI Decisions Explainable

Why AI Explainability Matters ВидеоInterpreting AI Predictions Using SHAP Видео Interpreting Model Predictions Using LIME ВидеоDemystifying AI Decisions ЧтениеHands-On-Learning: Demystifying Model Decisions Взаимная проверкаCommunicating What the Model "Thinks" Обсуждение

Lesson 3: Building Ethical and Compliant AI Workflows

Implementing Ethical AI: Creating Actionable Checklists ВидеоNIST AI RMF Overview ВидеоDocumenting Models with Model Cards ВидеоResponsible AI Checklist Creation ЧтениеCongratulations and Continuous Learning JourneyВидеоProject: Evaluate your AI System Взаимная проверкаResponsible AI: Transparency & EthicsЗадание