Responsible AI: Principles and Practices

Responsible AI: Principles and Practices

Lead the GenAI revolution by learning fairness, bias mitigation, and Explainable AI in Responsible AI: Principles and Practices. Future-proof your skills in ethical AI development.

Intermediate

40 Lessons

20h

Certificate of Completion

Lead the GenAI revolution by learning fairness, bias mitigation, and Explainable AI in Responsible AI: Principles and Practices. Future-proof your skills in ethical AI development.

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

1 Project
46 Playgrounds
5 Quizzes

This course includes

1 Project
46 Playgrounds
5 Quizzes

Course Overview

This course offers a comprehensive exploration of the ethical considerations and best practices surrounding the development and deployment of artificial intelligence (AI) systems, all within the context of Python. In this course, you will focus on the key pillars of Responsible AI, starting with the notion of fairness. You’ll gain insight into the presence of biases across the AI life cycle and learn strategies for identifying and mitigating bias in AI solutions. The course emphasizes the significance of ...Show More

What You'll Learn

An understanding of ethical considerations in artificial intelligence development

The ability to learn how to evaluate and make responsible decisions throughout the AI life cycle

The ability to identify biases in AI solutions and implement strategies to mitigate them effectively

Familiarity with interpreting and explaining AI model decisions, enhancing transparency and accountability in AI systems

Knowledge of best practices for preserving data privacy and enhancing the security of AI solutions, mitigating risks, and safeguarding sensitive information

The ability to explore emerging technologies and methodologies in Responsible AI, such as data annotation and synthetic data generation

What You'll Learn

An understanding of ethical considerations in artificial intelligence development

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Course Content

4.

Data Privacy, Safety, and Security for Responsible AI

Grasp the fundamentals of data privacy, safety, and security in responsible AI development.
6.

Conclusion

1 Lesson

Investigate the importance of fairness, explainability, privacy, and ethical AI practices.

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Souvik Kundu

Front-end Developer

Eric Downs

Musician/Entrepeneur

Anthony Walker

@_webarchitect_

Evan Dunbar

ML Engineer

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