Microsoft Future Ready: Ethics and Law in Data and Analytics

This course is part of the Ethics Laws and Implementing an AI Solution on Microsoft Azure ExpertTrack, helping you understand AI ethics and laws while developing advanced AI and machine learning skills.

During this course, you’ll learn how to apply ethical and legal frameworks to the powerful AI and Analytics tools used by corporations, governments and individuals. You’ll also learn how to use practical approaches to tackle data and analytics problems.

Delve into the legalities and ethics of data sharing, privacy and algorithmic decision-making

Data professionals use different analytical tools to create real-world outcomes. Though it’s important to achieve optimal results, we must also consider the ethics surrounding data sharing, privacy and algorithmic decision-making.

This course will teach how to apply legal and ethical frameworks to initiatives in the data profession. You’ll also learn how to investigate applied data methods for ethical and legal work in Analytics and AI, a useful skill in this increasingly competitive and technologically complicated world.

Explore practical approaches to data and analytics

There are many problems posed by work in Big Data, Data Science and AI. During this course, you’ll explore practical approaches to help tackle these data and analytics challenges.

By the end of the course, you’ll be comfortable with the ethical and legal frameworks surrounding AI and Analytics, giving you a deeper understanding of the problems faced by data professionals.

This course is aimed at anyone, including data scientists, who are interested in learning more about the questions of law and ethics surrounding data and analytics.

No prior knowledge or specific tools are required.

This course is aimed at anyone, including data scientists, who are interested in learning more about the questions of law and ethics surrounding data and analytics.

• Foundational abilities in applying ethical and legal frameworks for the data profession
• Practical approaches to data and analytics problems, including Big Data and Data Science and AI
• Applied data methods for ethical and legal work in Analytics and AI