AI Strategy and Governance

Ends tomorrow! Save 40% on your access to 10,000+ programs and make a real impact in your career. Save now.

AI Strategy and Governance

This course is part of AI For Business Specialization

Instructors: Kartik Hosanagar +3 more

29,706 already enrolled

Included with

4 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

No prior experience required

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

4 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

No prior experience required

1 week to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

Skills you'll gain

Category: Law, Regulation, and Compliance
Category: General Data Protection Regulation (GDPR)
Category: Innovation
Category: Business Transformation
Category: Data Security
Category: Personally Identifiable Information
Category: Artificial Intelligence
Category: Machine Learning
Category: Data Ethics
Category: Data Strategy
Category: AI Enablement
Category: Corporate Strategy
Category: AI Product Strategy
Category: Responsible AI
Category: Governance
Category: Data Governance
Category: Big Data
Category: Business Strategies

Tools you'll learn

Category: Risking
Category: Model Deployment

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

8 assignments¹

AI Graded see disclaimer

Taught in English

Build your subject-matter expertise

This course is part of the AI For Business Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
Earn a shareable career certificate

There are 4 modules in this course

In this course, you will discover AI and the strategies that are used in transforming business in order to gain a competitive advantage. You will explore the multitude of uses for AI in an enterprise setting and the tools that are available to lower the barriers to AI use. You will get a closer look at the purpose, function, and use-cases for explainable AI. This course will also provide you with the tools to build responsible AI governance algorithms as faculty dive into the large datasets that you can expect to see in an enterprise setting and how that affects the business on a greater scale. Finally, you will examine AI in the organizational structure, how AI is playing a crucial role in change management, and the risks with AI processes. By the end of this course, you will learn different strategies to recognize biases that exist within data, how to ensure that you maintain and build trust with user data and privacy, and what it takes to construct a responsible governance strategy. For additional reading, Professor Hosanagar's book "A Human’s Guide to Machine Intelligence" can be used as an additional resource for more extensive information on topics covered in this module.

In this module, you will begin by examining the key inputs to AI and what tools are currently used to lower the barriers of entry for AI use. Next, you will learn the economics of AI and the competition that has emerged as AI becomes more crucial to support industry needs and we see more cloud adoption. You will learn about the value of data as it is tied to Deep Learning, and how AutoML is changing the landscape of Machine Learning, and the growing competition and implications of data harvesting. By the end of this module, you will have gained knowledge about the economic implications of AI and Machine Learning and how they impact our lives in unseen ways. You will also understand the complex nature of computational hardware and how that affects consumer demand, but also the demand for privacy.

What's included

14 videos2 readings2 assignments

14 videosTotal 77 minutes

Intro to AI Strategy2 minutes
AI- Driven Business Transformation4 minutes
Developing a Portfolio16 minutes
Lowering Barriers for AI Use4 minutes
Economics of AI: Software4 minutes
Economics of AI: Skills2 minutes
Economics of AI: Compute4 minutes
Economics of AI: Data3 minutes
Economics of AI: AutoML4 minutes
Economics of AI: Auto ML Hubris2 minutes
Economics of AI: Competitive Implications2 minutes
Interview with Apoorv Saxena5 minutes
AI in the Organization Structure6 minutes
Interview With Barkha Saxena19 minutes

2 readingsTotal 40 minutes

Additional Readings10 minutes
Module 1 Slides30 minutes

2 assignmentsTotal 60 minutes

Practice Quiz #130 minutes
Module 1 Quiz30 minutes

In this module, you will examine AI and data analytics to show the economical use-cases of Big Data. You will also learn about the methods and tools that are being used to lower the barriers of entry for AI use. You will review current examples of Big Data and how those firms are using their analytical tools to enhance productivity and transformation. Lastly, you will get an in-depth look at how AI can be used in BioPharma and how the payoff of their AI investment is revitalizing their industry. By the end of this module, you will have a firm grasp on the practical deployment of AI across different industries, their use-cases, and how you can best implement them to drive innovation and transformation within business.

What's included

8 videos1 reading2 assignments

8 videosTotal 108 minutes

Is AI and Data Analytics Suited for Innovation?7 minutes
AI and Process Innovation10 minutes
Product Innovation6 minutes
Different Types of Product Innovation14 minutes
Organization Factors24 minutes
Dispersion of Employees11 minutes
Managerial Practice22 minutes
AI and Drug Example12 minutes

1 readingTotal 30 minutes

Module 2 Slides30 minutes

2 assignmentsTotal 60 minutes

Practice Quiz #230 minutes
Module 2 Quiz30 minutes

In this module, you will examine the inherent bias that can exist within data based on human behaviors. Building on these foundations, you will explore different responses within algorithmic bias and how organizations should respond and overcome these challenges. You will then review the manipulation of data, the different kinds of manipulation, and ways to ethically approach these issues. Lastly, you will examine data protection and the legal frameworks that exist to protect the consumer and individual data, and the stages of the privacy lifecycle. By the end of this module, you will have a thorough understanding of data biases, manipulation, and ethical questions of how data is handled and stored. You will be able to implement fairer algorithms and understand the legal ramifications of improperly managing data you collect.

What's included

5 videos1 reading2 assignments

In this module, you will learn about explainable AI and its relationship to Deep Learning. You will also review why it is important to have explainable AI and the different approaches to creating fair algorithms and AI policies. You will also examine Explainable AI and review the necessity of equitable algorithms. You will also learn why we do not always use Explainable AI for every model, and the impacts that it can have on performance. By the end of this module, you will have gained insight into decision-making with AI and the importance of fairness and transparency in creating explainable AI systems, as well as the ethical principles and governance policies that build trust in using AI and Machine Learning.

What's included

7 videos1 reading2 assignments1 peer review

7 videosTotal 46 minutes

AI Governance18 minutes
AI Ethics Principles5 minutes
Explainable AI: What is Explainable AI?2 minutes
Explainable AI: Examples of When Explainability is Important4 minutes
Explainable AI: Tradeoffs Between Interpretability and Performance3 minutes
Explainable AI: Approaches to Explainable AI4 minutes
Explainability and the Law10 minutes

1 readingTotal 30 minutes

Module 4 Slides30 minutes

2 assignmentsTotal 60 minutes

Practice Quiz #430 minutes
Module 4 Quiz30 minutes

1 peer reviewTotal 60 minutes

Module 460 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Kartik Hosanagar

University of Pennsylvania

8 Courses299,556 learners

Offered by

University of Pennsylvania

Why people choose Coursera for their career

Felipe M.

Learner since 2018

"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."

Jennifer J.

Learner since 2020

"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."

Larry W.

Learner since 2021

"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

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. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

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.

¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.