Fundamentals of Explainable AI & Algorithmic Fairness

Dive deeper into the ethical side of AI! This course equips you with the fundamentals of Explainable AI (XAI) and Algorithmic Fairness.  Unveil the inner workings of AI decision-making and ensure it aligns with ethical principles.  We’ll explore hot topics like bias detection, interpretability techniques, and responsible development practices.  Empower yourself to build trustworthy AI systems and champion responsible innovation across industries.

By the end of this course, you will: 

• Understand key concepts in eXplainable AI (XAI): Learn methods to clarify AI predictions and understand how models behave.
• Detect and address bias: Identify and remedy potential biases in AI algorithms to ensure fairness and inclusivity.
• Uphold ethical AI standards: Gain insight into the ethical aspects of AI development and deployment.
• Implement best practices: Acquire practical skills in creating and evaluating fair and transparent AI solutions.
• Foster critical thinking: Examine real-world scenarios and engage in discussions on AI’s societal implications.