400+ Students
The ability to apply recognized Responsible AI principles (FTAS) to any AI project.
Practical techniques for identifying, measuring, and reducing harmful algorithmic bias.
Tools and methods to ensure model decisions are understandable and justifiable.
Knowledge of global regulations and best practices for establishing organizational AI policies and risk assessment.
While not a coding course, familiarity with basic AI/ML terminology (e.g., model, data, features, prediction) is highly recommended.
Professionals responsible for building models and who need to implement ethical checks and balances.
Individuals who define AI product features and must ensure they are fair, safe, and transparent.
Professionals tasked with navigating the complex and evolving global landscape of AI regulation.
Leaders responsible for setting the strategic direction and risk tolerance for AI adoption.
Participate in dynamic, hands-on sessions led by expert instructors to gain practical skills in a supportive learning environment.
Acquire the necessary knowledge to develop and integrate ethical and compliance standards into the AI development lifecycle.
Learn to use technical tools and processes to identify, measure, and effectively reduce sources of bias in data and model outputs.
You will complete a hands-on project (e.g., a bias audit of a sample dataset) that can be added to your professional portfolio to demonstrate your skills to potential employers.
Gain continuous learning with one year of unlimited access to all course materials, tools, and resources, allowing you to study at your own pace and revisit topics as needed.
Everything you need to know about our top rated course.
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