This Course is designed for students at the Beginner level.
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In the rapidly evolving world of artificial intelligence (AI) and machine learning, the importance of trust and responsibility cannot be overstated. The “Responsible Innovation and Trustworthy AI” course is designed for professionals who are involved in making decisions based on AI and analytics systems, as well as those who are responsible for designing, developing, and training these systems. This course is especially beneficial for anyone from business executives and data scientists to analysts and programmers who wish to gain a deeper understanding of how to implement and use AI responsibly.
The course covers essential topics such as how trustworthy AI integrates with the analytics lifecycle and data supply chain, and how to identify and mitigate unwanted biases throughout the process. Learners will explore the principles of responsible innovation, including human-centricity, inclusivity, accountability, privacy, security, robustness, and transparency. By applying these principles, participants will be empowered to design and use AI and machine learning systems in ways that prioritize ethical practices and ensure fairness in decision-making.
Each module in the course is designed to be completed in under an hour, making it easy for busy professionals to work at their own pace. As new modules are released, learners can continue to build on their knowledge, keeping track of their progress as they explore various real-world scenarios. These scenarios include exploring the impact of AI in sensitive areas such as palliative care risk scores, racial bias in research, and privacy concerns in mobile devices. Furthermore, the course highlights how SAS technologies address unwanted bias and promote responsible innovation in data management, model development, and deployment.
Ultimately, this course equips participants with the tools and knowledge needed to ensure that AI systems are not only effective but also ethical and trustworthy. By taking this course, business leaders and technical professionals alike can make informed decisions about how to integrate responsible AI practices into their organizations.
