Will I earn university credit for completing the Specialization?

This specialization does not provide university credit.

What will I be able to do upon completing the Specialization?

Upon completing the specialization, you should be able to better understand how machine learning models work, and if desired, obtain an entry-level data analysis / machine learning position.

Is this course really 100% online? Do I need to attend any classes in person?

This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

Can I just enroll in a single course?

Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

Is financial aid available?

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Can I take the course for free?

No, you cannot take this course for free. When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you cannot afford the fee, you can apply for financial aid.

Ethics in the Age of AI Specialization

What's the ethical impact of AI making decisions?. Learn how to impose ethical behavior on machine models.

Instructors: LearnQuest Network

Included with Coursera Plus

Learn more

4 course series

Get in-depth knowledge of a subject

4.8

(274 reviews)

Beginner level

Recommended experience

1 month at 10 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

4 course series

Get in-depth knowledge of a subject

4.8

(274 reviews)

Beginner level

Recommended experience

1 month at 10 hours a week

Flexible schedule

Earn a career credential

Share your expertise with employers

What you'll learn

Define predictive models and analyze how companies use them
Identify how learning algorithms are used in everyday life
Examine the ability of algorithms to influence and decide human behavior in biased ways, and methods to avoid predictive bias
Identify vulnerabilities in public data sets and analyze algorithmic privacy violations

Overview

As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations. In this specialization, we will explore the rise of algorithms, fundamental issues of fairness and bias in machine learning, and basic concepts involved in security and privacy of machine learning projects. We'll finish with a study of 3 projects that will allow you to put your new skills into action.

What’s included

Shareable certificate

Add to your LinkedIn profile

Taught in English

33 practice exercises

Advance your subject-matter expertise

Learn in-demand skills from university and industry experts
Master a subject or tool with hands-on projects
Develop a deep understanding of key concepts
Earn a career certificate from LearnQuest

Specialization - 4 course series

Artificial Intelligence Algorithms Models and Limitations

Course 16 hours4.7 (499 ratings)View course

What you'll learn

We live in an age increasingly dominated by algorithms. As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations in the real world. Whether it's making loan decisions or re-routing traffic, machine learning models need to accurately reflect our shared values. In this course, we will explore the rise of algorithms, from the most basic to the fully-autonomous, and discuss how to make them more ethically sound.

Skills you'll gain

Predictive Modeling, Algorithms, Data Ethics, Responsible AI, Artificial Intelligence, Machine Learning Algorithms, Ethical Standards And Conduct, Predictive Analytics, Risk Modeling, Economics, Computational Thinking, Data Collection, Artificial Intelligence and Machine Learning (AI/ML), Statistical Modeling, Machine Learning, Economic Development, and AI Product Strategy

Artificial Intelligence Data Fairness and Bias

Course 24 hours4.8 (121 ratings)View course

What you'll learn

Skills you'll gain

Machine Learning, Responsible AI, Data Ethics, Predictive Modeling, Data Collection, Algorithms, Artificial Intelligence, and Game Theory

Artificial Intelligence Privacy and Convenience

Course 34 hours4.7 (100 ratings)View course

What you'll learn

In this course, we will explore fundamental concepts involved in security and privacy of machine learning projects. Diving into the ethics behind these decisions, we will explore how to protect users from privacy violations while creating useful predictive models. We will also ask big questions about how businesses implement algorithms and how that affects user privacy and transparency now and in the future.

Skills you'll gain

Responsible AI, Information Privacy, Data Governance, Data Ethics, Machine Learning, Predictive Modeling, Artificial Intelligence, Personally Identifiable Information, and Data Security

Artificial Intelligence Ethics in Action

Course 45 hours4.6 (324 ratings)View course

What you'll learn

AI Ethics research is an emerging field, and to prove our skills, we need to demonstrate our critical thinking and analytical ability. Since it's not reasonable to jump into a full research paper with our newly founded skills, we will instead work on 3 projects that will demonstrate your ability to analyze ethical AI across a variety of topics and situations. These projects include all the skills you've learned in this AI Ethics Specialization.

Skills you'll gain

Data Ethics, Responsible AI, Analytical Skills, Ethical Standards And Conduct, Game Theory, Large Language Modeling, Predictive Modeling, Analysis, OpenAI, and Artificial Intelligence