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University of Pennsylvania
AI Applications in Marketing and Finance
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University of Pennsylvania

AI Applications in Marketing and Finance

This course is part of AI For Business Specialization

Michael R Roberts
Raghu Iyengar
Kartik Hosanagar

Instructors: Michael R Roberts

Instructors

Instructor ratings

We asked all learners to give feedback on our instructors based on the quality of their teaching style.

4.7 (100 ratings)
Michael R Roberts
Michael R Roberts
University of Pennsylvania
4 Courses•289,949 learners
Raghu Iyengar
Raghu Iyengar
University of Pennsylvania
2 Courses•326,932 learners
Kartik Hosanagar
Kartik Hosanagar
University of Pennsylvania
8 Courses•264,868 learners

28,965 already enrolled

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4 modules
Gain insight into a topic and learn the fundamentals.
4.6

(440 reviews)

6 hours to complete
Flexible schedule
Learn at your own pace
91%
Most learners liked this course

4 modules
Gain insight into a topic and learn the fundamentals.
4.6

(440 reviews)

6 hours to complete
Flexible schedule
Learn at your own pace
91%
Most learners liked this course
  • About
  • Outcomes
  • Modules
  • Recommendations
  • Testimonials
  • Reviews

Skills you'll gain

  • Marketing Analytics
  • MarTech
  • Customer Insights
  • Financial Services
  • Consumer Behaviour
  • Machine Learning
  • Threat Detection
  • Artificial Intelligence
  • Retail Store Operations
  • Customer Engagement
  • AI Personalization
  • Big Data
  • Financial Analysis
  • Credit Risk
  • Risk Modeling
  • Customer experience improvement

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

4 assignments

Taught in English

See how employees at top companies are mastering in-demand skills

Learn more about Coursera for Business
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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 learn about AI-powered applications that can enhance the customer journey and extend the customer lifecycle. You will learn how this AI-powered data can enable you to analyze consumer habits and maximize their potential to target your marketing to the right people. You will also learn about fraud, credit risks, and how AI applications can also help you combat the ever-challenging landscape of protecting consumer data. You will also learn methods to utilize supervised and unsupervised machine learning to enhance your fraud detection methods. You will also hear from leading industry experts in the world of data analytics, marketing, and fraud prevention. By the end of this course, you will have a substantial understanding of the role AI and Machine Learning play when it comes to consumer habits, and how we are able to interact and analyze information to increase deep learning potential for your business.

In this module, you will delve into the impact of AI in marketing, and how it affects how your customers interact with your organization and its offerings. You will learn about how AI is disrupting retail and transforming the way that we conduct business in the digital age. You will next discover the risks and challenges that you might encounter when trying to implement AI, such as privacy issues, and how to make the journey from interest to purchase a much shorter one. By the end of this module, you will have a firm understanding of how AI influences and also impact customer behavior, and how you can take advantage of the myriad of ways AI can be applied to support your business and align with your customers.

What's included

8 videos1 reading1 assignment

8 videos•Total 58 minutes
  • Introduction to AI Applications•2 minutes
  • Module Introduction•5 minutes
  • Customer Journey•9 minutes
  • Making the Customer Journey Shorter•7 minutes
  • Moving Upstream in the Customer Journey•13 minutes
  • Recognizing New Forms of Risk with Machine Intelligence•7 minutes
  • Organizational Structure for Analytics•7 minutes
  • A Template for AI Transformation•5 minutes
1 reading•Total 10 minutes
  • Module 1 Slides•10 minutes
1 assignment•Total 30 minutes
  • Module 1 Quiz•30 minutes

In this module, you will discover different ways that AI can be applied to enhance the consumer experience. You will take a deep dive into the realm of personalization algorithms, and how they are utilized in companies such as Pandora, Netflix, and Amazon. Next, you will learn about the challenges that you can face when trying to implement these algorithms or recommendation systems. You will also hear from Barkha Saxena, Chief Data Office for Poshmark, and how she takes data provided by their over 80 million users to create a curated experience, but still allow their customers to discover new products and engage with buyers. By the end of this module, you would have gained valuable insight into how AI can enable personalization and in turn drive customer engagement and retention.

What's included

4 videos1 reading1 assignment

4 videos•Total 60 minutes
  • Personalization: Recommendation Systems•12 minutes
  • Personalization: Impacts on Markets•11 minutes
  • Personalization: Addressing the Challenges•7 minutes
  • Interview with Scott Wong•28 minutes
1 reading•Total 10 minutes
  • Module 2 Slides•10 minutes
1 assignment•Total 30 minutes
  • Module 2 Quiz•30 minutes

In this module, you will learn how to mitigate fraud using AI systems. By examining various machine learning methods, you will discover different ways to analyze risk assessment using KPIs and the scientific method. You will then learn about corporate credit and the relationship between money borrowed, the price and availability of credit, as well corporate credit ratings and why and how that rating translates to risk. Lastly, you will learn about using models versus real-world data, and how you can use AI to conduct error analysis to prevent costly miscalculations. By the end of this module, you will have a firm knowledge of different risk assessment methods, how data can be used to analyze and predict credit ratings, as well as the benefits and limitations of different applications used in the industry.

What's included

13 videos1 reading1 assignment

13 videos•Total 101 minutes
  • Introduction•6 minutes
  • Process: Scientific Method•7 minutes
  • Process: Data Science Workflow•6 minutes
  • Corporate Credit Risk•5 minutes
  • Credit Risk - KPIs•15 minutes
  • Credit Risk - Credit Ratings•8 minutes
  • Credit Risk - Credit Ratings Prediction•8 minutes
  • Credit Risk - Data•8 minutes
  • Credit Risk - Model Prep•7 minutes
  • Credit Risk - Model Training•8 minutes
  • Credit Risk - Models vs. Data•6 minutes
  • Credit Risk - Error Analysis•6 minutes
  • Credit Risk - Concluding Thoughts•5 minutes
1 reading•Total 10 minutes
  • Module 3 Slides•10 minutes
1 assignment•Total 30 minutes
  • Module 3 Quiz•30 minutes

In this module, you will hear from executives Carleigh Jaques, In this module, you will hear from executives Carleigh Jaques, SVP of CyberSource at Visa, and Apoorv Saxena, formerly the head of Google’s AI Verticals Team and was until recently the Global Head of AI at JPMorgan Chase. These interviews will allow you to get valuable insight into how major global brands utilize AI to create a secure shopping environment for their customers and clients, and how AI is instrumental in the data-driven world of finance. By the end of this module, you will have heard from top industry experts in their field and gained firsthand accounts of risk management and assessment and how AI is playing a more integral role in combating digital fraud.

What's included

4 videos1 assignment

4 videos•Total 43 minutes
  • Interview with Apoorv Saxena•11 minutes
  • Machine Learning in Finance: Fraud Detection•10 minutes
  • Machine Learning in Finance: Additional Applications•8 minutes
  • Interview with Carleigh Jaques•13 minutes
1 assignment•Total 30 minutes
  • Module 4 Quiz•30 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

Instructor ratings

Instructor ratings

We asked all learners to give feedback on our instructors based on the quality of their teaching style.

4.7 (100 ratings)
Michael R Roberts
Michael R Roberts
University of Pennsylvania
4 Courses•289,949 learners

Instructors

Instructor ratings

We asked all learners to give feedback on our instructors based on the quality of their teaching style.

4.7 (100 ratings)
Michael R Roberts
Michael R Roberts
University of Pennsylvania
4 Courses•289,949 learners
Raghu Iyengar
Raghu Iyengar
University of Pennsylvania
2 Courses•326,932 learners
Kartik Hosanagar
Kartik Hosanagar
University of Pennsylvania
8 Courses•264,868 learners

Offered by

University of Pennsylvania

Offered by

University of Pennsylvania

The University of Pennsylvania (commonly referred to as Penn) is a private university, located in Philadelphia, Pennsylvania, United States. A member of the Ivy League, Penn is the fourth-oldest institution of higher education in the United States, and considers itself to be the first university in the United States with both undergraduate and graduate studies.

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4.6

440 reviews

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Showing 3 of 440

S
SP
5

Reviewed on Mar 23, 2025

Excellent details about how AI and ML are applied to specific use cases.

K
KL
4

Reviewed on Oct 8, 2023

Learned real-world application of AI/ML in Finance and the huge potential of more to come

P
PM
5

Reviewed on Nov 2, 2024

A must take course to understand the usage of AI in Finance. Lot of really important learning for the future.

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