Self-paced course

Self-paced course

Data & AI Ethics

Data & AI Ethics

Rating 4.5

24 reviews

24 reviews

24 reviews

Course Description

Data and AI Ethics are topics that most data leaders and professionals don’t learn in school, or on the job.

But as the volume of data grows and the impact of ML & AI algorithms continues to increase, understanding the ethical implications of our work – and how to prevent & mitigate ethical lapses – is more important than ever.

We’ll start this course by defining AI and Data ethics before moving onto what it means to be an ethical steward of data.

From there, we’ll dive into the types of bias that can be present in your data and how it can propagate into analyses and algorithms in a way that can not only raise ethical questions, but also negatively impact your company’s bottom line.

Next we’ll dive into the world of modern AI models, and the unique risks and ethical concerns posed by powerful generative AI tools. We’ll use case studies to highlight real life controversies, discuss how to mitigate the risk of ethical lapses, and use thought exercises to help you develop the skills to anticipate, identify, and mitigate the risk of ethical lapses in your day-to-day work.

If you’re looking for a unique and highly engaging way to learn about data and AI ethics, this is the course for you.

Course Description

Data and AI Ethics are topics that most data leaders and professionals don’t learn in school, or on the job.

But as the volume of data grows and the impact of ML & AI algorithms continues to increase, understanding the ethical implications of our work – and how to prevent & mitigate ethical lapses – is more important than ever.

We’ll start this course by defining AI and Data ethics before moving onto what it means to be an ethical steward of data.

From there, we’ll dive into the types of bias that can be present in your data and how it can propagate into analyses and algorithms in a way that can not only raise ethical questions, but also negatively impact your company’s bottom line.

Next we’ll dive into the world of modern AI models, and the unique risks and ethical concerns posed by powerful generative AI tools. We’ll use case studies to highlight real life controversies, discuss how to mitigate the risk of ethical lapses, and use thought exercises to help you develop the skills to anticipate, identify, and mitigate the risk of ethical lapses in your day-to-day work.

If you’re looking for a unique and highly engaging way to learn about data and AI ethics, this is the course for you.

Course Content

2 video hours

Skills you'll learn in this course

Identify bias & fairness issues in data collection and model design

Evaluate privacy, transparency & explainability requirements for AI

Apply ethical frameworks & regulations (GDPR, CDPA, ISO) to projects

Build governance checklists that turn principles into daily practice

Meet your instructors

Chris Bruehl

Analytics Engineer & Lead Python Instructor

Chris is a Python expert, certified Statistical Business Analyst, and seasoned Data Scientist, having held senior-level roles at large insurance firms and financial service companies. He earned a Masters in Analytics at NC State's Institute for Advanced Analytics, where he founded the IAA Python Programming club.

Student reviews

To Maven analytics family, thank you so much for the Open Campus Program. I want to you assure that the lessons learned will be used ethically in handling data related issues, to avoid harmful bias and mitigate risks on the usage of AI.

D. Freeman Myers

In the rise of AI, we should all know about ethical practice about it. In this handful learning course Chris Bruehl helps to understand Data Ethics, Ethical data Stewardship, and AI Ethics & Biases. Anyone interested in data role or interested in AI should take the learning journey.

M K Junayed Parves

I recently completed the Data & AI Ethics course on Maven Analytics, and it was a fantastic experience! The course covers essential topics in data ethics, providing a solid foundation on the principles needed to navigate this important area. What really stood out to me were the thought-provoking exercises woven throughout the course. They challenged me to think critically about real-world scenarios and ethical dilemmas, making the content feel both engaging and applicable. The practical insights and interactive exercises make this course a must for anyone working with data or AI, and I highly recommend it!

ayad aziz

Included learning paths

Course credential

You’ll earn the course certification by completing this course and passing the assessment requirements

Data & AI Ethics

Data & AI Ethics

CPE Accreditation

CPE Credits:

0

Field of Study:

Information Technology

Delivery Method:

QAS Self Study

Maven Analytics LLC is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org.

For more information regarding administrative policies such as complaints or refunds, please contact us at admin@mavenanalytics.io or (857) 256-1765.

*Last Updated: May 25, 2023

Course Description

Data and AI Ethics are topics that most data leaders and professionals don’t learn in school, or on the job.

But as the volume of data grows and the impact of ML & AI algorithms continues to increase, understanding the ethical implications of our work – and how to prevent & mitigate ethical lapses – is more important than ever.

We’ll start this course by defining AI and Data ethics before moving onto what it means to be an ethical steward of data.

From there, we’ll dive into the types of bias that can be present in your data and how it can propagate into analyses and algorithms in a way that can not only raise ethical questions, but also negatively impact your company’s bottom line.

Next we’ll dive into the world of modern AI models, and the unique risks and ethical concerns posed by powerful generative AI tools. We’ll use case studies to highlight real life controversies, discuss how to mitigate the risk of ethical lapses, and use thought exercises to help you develop the skills to anticipate, identify, and mitigate the risk of ethical lapses in your day-to-day work.

If you’re looking for a unique and highly engaging way to learn about data and AI ethics, this is the course for you.

Course Description

Data and AI Ethics are topics that most data leaders and professionals don’t learn in school, or on the job.

But as the volume of data grows and the impact of ML & AI algorithms continues to increase, understanding the ethical implications of our work – and how to prevent & mitigate ethical lapses – is more important than ever.

We’ll start this course by defining AI and Data ethics before moving onto what it means to be an ethical steward of data.

From there, we’ll dive into the types of bias that can be present in your data and how it can propagate into analyses and algorithms in a way that can not only raise ethical questions, but also negatively impact your company’s bottom line.

Next we’ll dive into the world of modern AI models, and the unique risks and ethical concerns posed by powerful generative AI tools. We’ll use case studies to highlight real life controversies, discuss how to mitigate the risk of ethical lapses, and use thought exercises to help you develop the skills to anticipate, identify, and mitigate the risk of ethical lapses in your day-to-day work.

If you’re looking for a unique and highly engaging way to learn about data and AI ethics, this is the course for you.

Curriculum

7

Course Feedback & Next Steps

7

Course Feedback & Next Steps

7

Course Feedback & Next Steps

Meet your instructors

Chris Bruehl

Analytics Engineer & Lead Python Instructor

Chris is a Python expert, certified Statistical Business Analyst, and seasoned Data Scientist, having held senior-level roles at large insurance firms and financial service companies. He earned a Masters in Analytics at NC State's Institute for Advanced Analytics, where he founded the IAA Python Programming club.

Student reviews

To Maven analytics family, thank you so much for the Open Campus Program. I want to you assure that the lessons learned will be used ethically in handling data related issues, to avoid harmful bias and mitigate risks on the usage of AI.

D. Freeman Myers

In the rise of AI, we should all know about ethical practice about it. In this handful learning course Chris Bruehl helps to understand Data Ethics, Ethical data Stewardship, and AI Ethics & Biases. Anyone interested in data role or interested in AI should take the learning journey.

M K Junayed Parves

I recently completed the Data & AI Ethics course on Maven Analytics, and it was a fantastic experience! The course covers essential topics in data ethics, providing a solid foundation on the principles needed to navigate this important area. What really stood out to me were the thought-provoking exercises woven throughout the course. They challenged me to think critically about real-world scenarios and ethical dilemmas, making the content feel both engaging and applicable. The practical insights and interactive exercises make this course a must for anyone working with data or AI, and I highly recommend it!

ayad aziz

Included learning paths

Course credential

You’ll earn the course certification by completing this course and passing the assessment requirements

Data & AI Ethics

Data & AI Ethics

CPE Accreditation

CPE Credits:

0

Field of Study:

Information Technology

Delivery Method:

QAS Self Study

Maven Analytics LLC is registered with the National Association of State Boards of Accountancy (NASBA) as a sponsor of continuing professional education on the National Registry of CPE Sponsors. State boards of accountancy have the final authority on the acceptance of individual courses for CPE credit. Complaints regarding registered sponsors may be submitted to the National Registry of CPE Sponsors through its website: www.nasbaregistry.org.

For more information regarding administrative policies such as complaints or refunds, please contact us at admin@mavenanalytics.io or (857) 256-1765.

*Last Updated: May 25, 2023

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