UPenn - AI Applications in Marketing and Finance
- Offered byCoursera
AI Applications in Marketing and Finance at Coursera Overview
Duration | 7 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
AI Applications in Marketing and Finance at Coursera Highlights
- Earn a Certificate upon completion
- Course 2 of 4 in the AI For Business Specialization
- Financial aid available
AI Applications in Marketing and Finance at Coursera Course details
- Learn about AI-powered applications that can enhance the customer journey and extend the customer lifecycle 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
- Learn about fraud, credit risks, and how AI applications can also help you combat the ever-challenging landscape of protecting consumer data Learn methods to utilize supervised and unsupervised machine learning to enhance your fraud detection methods
- 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
AI Applications in Marketing and Finance at Coursera Curriculum
Module 1 -AI and the Customer Journey
Introduction to AI Applications
Module Introduction
Customer Journey
Making the Customer Journey Shorter
Moving Upstream in the Customer Journey
Recognizing New Forms of Risk with Machine Intelligence
Organizational Structure for Analytics
A Template for AI Transformation
Module 1 Slides
Module 1 Quiz
Module 2 -Personalization
Personalization- Recommendation Systems
Personalization: Impacts on Markets
Personalization: Addressing the Challenges
Interview with Scott Wong
Module 2 Slides
Module 2 Quiz
Module 3 -Finance
Introduction
Process: Scientific Method
Process: Data Science Workflow
Corporate Credit Risk
Credit Risk - KPIs
Credit Risk - Credit Ratings
Credit Risk - Credit Ratings Prediction
Credit Risk - Data
Credit Risk - Model Prep
Credit Risk - Model Training
Credit Risk - Models vs. Data
Credit Risk - Error Analysis
Credit Risk - Concluding Thoughts
Module 3 Slides
Module 3 Quiz
Module 4 'Additional AI Applications in Finance
Interview with Apoorv Saxena
Machine Learning in Finance: Fraud Detection
Machine Learning in Finance: Additional Applications
Interview with Carleigh Jaques
Module 4 Quiz
AI Applications in Marketing and Finance at Coursera Admission Process
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AI Applications in Marketing and Finance