Home AI Courses Fundamentals of Responsible AI/ML

Fundamentals of Responsible AI/ML

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Gain proficiency in responsible AI practices to guarantee that AI/ML models are ethical, transparent, and regulatory-compliant.

Key AI Functions:artificial intelligence,data science,development,machine learning,ai & machine learning

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Description for Fundamentals of Responsible AI/ML

Comprehending Ethical Risks and Model Bias: Learn about the ethical challenges, societal impacts, and model bias of AI/ML models, as well as the importance of adhering to pertinent regulations.
Problem Identification and Mitigation: Develop the ability to identify and resolve issues such as data drift, correlated features, overfitting, and incorrect inferences in order to guarantee the robustness of AI/ML models.
Frameworks and Explainable AI: Utilize frameworks such as LIME, SHAP, and TCAV to investigate the principles of explainable AI (XAI), with an emphasis on transparency and justifications for a variety of stakeholders.
Regulation and Responsible AI: Comprehend the legal and ethical framework that influences AI/ML models and determine the most effective methods for incorporating responsible practices into the development and deployment of AI.

Level: Beginner

Certification Degree: Yes

Languages the Course is Available: 4

Offered by: On Udemy provided by Vasco Patricio

Duration: 8h 35m

Schedule: Full lifetime access

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