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Design & Present Responsible AI Solutions

kurs ist nicht verfügbar in Deutsch (Deutschland)

Wir übersetzen es in weitere Sprachen.

Design & Present Responsible AI Solutions

Dieser Kurs ist Teil mehrerer Programme.

Dozenten: Starweaver

Bei enthalten

Mehr erfahren

3 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

4 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

3 Module

Verschaffen Sie sich einen Einblick in ein Thema und lernen Sie die Grundlagen.

Stufe Mittel

Empfohlene Erfahrung

4 Stunden zu vervollständigen

Flexibler Zeitplan

In Ihrem eigenen Lerntempo lernen

Was Sie lernen werden

Evaluate AI use cases by applying key Responsible AI principles such as fairness, transparency, and accountability.
Identify and document potential risks and biases across data, models, and user interactions using structured ethical design tools.
Develop and communicate stakeholder-ready presentations and documentation that clearly articulate Responsible AI design decisions.

Kompetenzen, die Sie erwerben

Kategorie: Responsible AI
Kategorie: Ethical Standards And Conduct
Kategorie: Data Storytelling
Kategorie: Stakeholder Analysis
Kategorie: Risk Mitigation
Kategorie: Model Evaluation
Kategorie: AI literacy
Kategorie: Storytelling
Kategorie: Data Ethics
Kategorie: Accountability Frameworks
Kategorie: Project Documentation
Kategorie: Presentations
Kategorie: Design
Kategorie: Communication Strategies
Kategorie: Accountability
Kategorie: Artificial Intelligence
Kategorie: Risk Management
Kategorie: Stakeholder Communications
Kategorie: Technical Communication
Kategorie: Data Presentation

Wichtige Details

Zertifikat zur Vorlage

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Kürzlich aktualisiert!

Dezember 2025

Bewertungen

1 Aufgabe

Unterrichtet in Englisch

91% of learners achieved a positive career outcome

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In diesem Kurs gibt es 3 Module

In an era where artificial intelligence influences hiring, healthcare, finance, and everyday decision-making, the demand for Responsible AI design has never been greater. This course empowers professionals, researchers, and innovators to design, evaluate, and communicate AI solutions that are transparent, fair, and trustworthy. Through practical frameworks and guided demos, learners will explore how to apply core Responsible AI principles-fairness, transparency, accountability, privacy, and safety-across the AI lifecycle. You’ll practice identifying bias and ethical risks, documenting safeguards using structured templates, and transforming complex technical work into clear, stakeholder-ready presentations. Real-world examples and corporate case studies demonstrate how leading organizations operationalize Responsible AI.

This course is for AI, data, ethics, and tech professionals who want to design and present transparent, fair, and responsible AI solutions. Ideal for developers, policymakers, and business leaders, it helps you apply Responsible AI principles and communicate them clearly to diverse stakeholders. Learners should have a basic understanding of AI/ML concepts, familiarity with data ethics, and the ability to present ideas clearly to non-technical audiences. By the end of this course, you’ll confidently design ethically sound AI solutions and present them persuasively to both technical and non-technical audiences.

Moduldetails

This module introduces learners to the foundational concepts of Responsible AI - exploring why ethical design, transparency, and accountability matter in modern AI systems. Learners will examine the core principles of Responsible AI, understand how bias and harm can emerge throughout the AI lifecycle, and discover how to embed ethical considerations into every stage of AI solution design. Through real-world case examples and structured reflection, this module establishes the mindset and vocabulary needed to design AI systems that are both innovative and trustworthy.

Das ist alles enthalten

4 Videos2 Lektüren1 peer review

4 VideosInsgesamt 23 Minuten

Welcome to Responsible AI Design4 Minuten
Why Responsible AI Matters5 Minuten
The Core Principles of Responsible AI7 Minuten
From Principles to Practice: Designing with Ethics in Mind6 Minuten

2 LektürenInsgesamt 10 Minuten

Welcome to the Course: Course Overview5 Minuten
Responsible AI: Why It Matters and How We’re Infusing It at Microsoft5 Minuten

1 peer reviewInsgesamt 20 Minuten

Hands-On-Learning: Responsible AI Risk Reflection20 Minuten

This module guides learners through the practical process of integrating Responsible AI principles into real-world system design. Learners will explore how to identify and mitigate ethical risks, detect and document bias, and evaluate model performance beyond accuracy metrics. They will learn to apply tools such as Responsible AI canvases, risk logs, and model cards to ensure transparency and accountability across the AI development lifecycle. By the end of the module, learners will be able to design AI systems that align with organizational values, regulatory standards, and human-centered goals.

Das ist alles enthalten

3 Videos1 Lektüre1 peer review

3 VideosInsgesamt 22 Minuten

Embedding Ethics into the AI Lifecycle7 Minuten
Using Responsible AI Canvases and Checklists7 Minuten
Reducing Bias and Communicating Uncertainty8 Minuten

1 LektüreInsgesamt 5 Minuten

Building Trustworthy AI: How Google Designs for Transparency and Fairness (2024)5 Minuten

1 peer reviewInsgesamt 20 Minuten

Hands-On-Learning: Responsible AI Design Challenge20 Minuten

This module focuses on transforming Responsible AI design work into clear, stakeholder-ready communication. Learners will discover how to structure and deliver presentations that effectively convey technical rigor, ethical awareness, and societal impact. The module covers techniques for visual storytelling, ethical reporting, and audience-tailored messaging to build trust and understanding among diverse stakeholders-executives, regulators, and the public alike. By the end of the module, learners will be able to craft compelling presentations and documentation that demonstrate both AI innovation and accountability.