Responsible AI Foundations
Offered By: LinkedIn Learning
Course Description
Overview
Responsible AI principles are key as AI integrates into more industries and interacts more with the public. This learning path underscores the core principles of responsible AI, frameworks to apply them practically in an enterprise organization, and tools for building fairness into AI systems.
- Discover the key principles of Responsible AI.
- Explore differentâand responsibleâapplications of AI.
- Understand the steps to design responsible algorithms.
Syllabus
Courses under this program:
Course 1: Foundations of Responsible AI
-Learn about the practices needed to perform fairness testing and implement responsible AI systems.
Course 2: Ethics in the Age of Generative AI
-Learn why ethical considerations are a critical part of the generative AI creation and deployment process and explore ways to address these ethical challenges.
Course 3: Responsible AI: Principles and Practical Applications
-Learn how AI is being used today and how to ensure its responsible usage into the future.
Course 4: AI Accountability: Build Responsible and Transparent Systems
-Learn why it's absolutely crucial for AI-related data science work to be transparent, explainable, accountable, and ethical in its design and execution.
Course 5: The State of AI and Copyright
-Gain valuable insights on the current state of AI and copyright laws in this panel discussion with UK-based attorney Matt Hervey and US-based attorney Jennifer Maisel.
Course 6: Introduction to AI Governance
-Explore core concepts and practical strategies to effectively implement and manage AI governance.
Course 1: Foundations of Responsible AI
-Learn about the practices needed to perform fairness testing and implement responsible AI systems.
Course 2: Ethics in the Age of Generative AI
-Learn why ethical considerations are a critical part of the generative AI creation and deployment process and explore ways to address these ethical challenges.
Course 3: Responsible AI: Principles and Practical Applications
-Learn how AI is being used today and how to ensure its responsible usage into the future.
Course 4: AI Accountability: Build Responsible and Transparent Systems
-Learn why it's absolutely crucial for AI-related data science work to be transparent, explainable, accountable, and ethical in its design and execution.
Course 5: The State of AI and Copyright
-Gain valuable insights on the current state of AI and copyright laws in this panel discussion with UK-based attorney Matt Hervey and US-based attorney Jennifer Maisel.
Course 6: Introduction to AI Governance
-Explore core concepts and practical strategies to effectively implement and manage AI governance.
Courses
-
Learn why it's absolutely crucial for AI-related data science work to be transparent, explainable, accountable, and ethical in its design and execution.
-
Learn about the practices needed to perform fairness testing and implement responsible AI systems.
-
Explore core concepts and practical strategies to effectively implement and manage AI governance.
-
Learn how AI is being used today and how to ensure its responsible usage into the future.
-
Learn why ethical considerations are a critical part of the generative AI creation and deployment process and explore ways to address these ethical challenges.
-
Gain valuable insights on the current state of AI and copyright laws in this panel discussion with UK-based attorney Matt Hervey and US-based attorney Jennifer Maisel.
Taught by
Ayodele Odubela, Vilas Dhar, Jill Finlayson, Barton Poulson, PhD, Garrick Chow and Vidhi Chugh
Related Courses
Building and Managing Superior SkillsState University of New York via Coursera ChatGPT et IA : mode d'emploi pour managers et RH
CNAM via France Université Numerique Digital Skills: Artificial Intelligence
Accenture via FutureLearn AI Foundations for Everyone
IBM via Coursera Design a Feminist Chatbot
Institute of Coding via FutureLearn