Increase your competitive edge in emerging business technology with our course

Artificial Intelligence for Business

Build a foundational understanding of Artificial Intelligence and Machine Learning in business

Learn from internationally-recognized internet marketing and media business professor, Kartik Hosanagar, PhD

Request More Information

Learn About the Artificial Intelligence for Business Course

In this course, you’ll learn the fundamentals of Big Data, Artificial Intelligence, and Machine Learning, and how to deploy these technologies to support your organization’s strategy. Professor Kartik Hosanagar of the Wharton School has designed this course to help you gain a better understanding of AI and Machine Learning, using real-life examples. You’ll learn about the different types and methods of Machine Learning, and how businesses have applied Machine Learning successfully. You’ll also cover the ethics and risks of AI, and how to design governance frameworks for proper implementation. By the end of this course, you’ll have a foundational understanding of AI and Machine Learning in business, and be able to incorporate these technologies into your business strategy.

The Artificial Intelligence for Business program is designed to provide learners with insights into the established and emerging developments in AI, Big Data, Machine Learning in finance, and the operational changes AI will bring . The lessons within this course are applicable to multiple industries and dynamic markets. This course is taught by internationally-recognized internet marketing and media business professor, Kartik Hosanagar, PhD, and takes into account the latest data and insights in the AI realm.

Program Format

  • Four fully online modules
  • Duration: 4-6 weeks
  • Commitment: 2 hours per week

Program Tuition

  • $599

Program Start Date

Enroll Immediately

Artificial Intelligence for Business Course Modules

Module 1

This module will begin with a definition of Big Data, an exploration of its origins, and why the ways it is produced matter. You’ll examine the most useful approaches to Big Data analysis, and learn which skillset and competencies are are required for Big Data analysis. You’ll also explore different data management and data analysis tools and discover how predictive analysis is used to extract intelligence from Big Data. By the end of this module, you’ll be better able to analyze big datasets, choose the right tools for analysis, and harness insights generated from Big Data to construct successful strategies for your business.

Module Overview:

  • AI for Business Introduction
  • Big Data Overview
  • Big Data Analysis
  • Data Management Infrastructure
  • Data Analysis: Extracting Intelligence from Big Data


In this module, you’ll examine the fundamentals of Artificial Intelligence, and delve deeper into Machine Learning. Through close examination of the history of AI and the expert systems approach, you’ll gain a deeper understanding of AI’s definition and types. You’ll also learn three types of Machine Learning (supervised, unsupervised, and reinforcement learning) and examine the differences between Machine Learning and AI. You’ll also explore factors that influence accuracy in Machine Learning, as well as analyze specific Machine Learning methods such as logistic regression, decision trees, and neural networks. By the end of this module, you will have a better understanding of both Artificial Intelligence and Machine Learning and be able to select appropriate algorithms and methods to optimize your business’ trajectory.

Module Overview:

  • Introduction to Artificial Intelligence
  • A Detailed View of Machine Learning
  • Specific Machine Learning Methods: A Deep Dive


In this module, you will explore real-world examples of Machine Learning in different business contexts, including personalization on the web, financial applications, and autonomous vehicles. You’ll learn about multiple applications of Machine Learning in finance, such as fraud detection and identity verification, as well as the opportunities and challenges of autonomous vehicles. Through analysis of various Recommender Systems, you’ll better understand their impact on markets and be able to address the challenges of each. By the end of this module, you’ll have a richer understanding of existing Machine Learning technologies and how they are transforming industries and markets.

Module Overview:

  • Business Applications of Machine Learning and Personalization
  • Personalization: Impacts on Markets
  • Personalization: Addressing the Challenges
  • Interview with Apoorv Saxena
  • Machine Learning in Finance: Fraud Detection
  • Machine Learning in Finance: Additional Applications
  • Autonomous Vehicles (AVs)
  • Challenges to Adoption


In this module, you’ll explore how to strategically implement AI within your organization and manage AI governance. You’ll examine how to develop a portfolio approach of AI projects and learn how quick wins and long-term projects can help companies successfully utilize the power of machine intelligence. You’ll also analyze specific organizational behaviors that help organizations generate value from AI. Through a series of examples such as Xaoice and Tay, you’ll learn about the risks from AI and the social risks AI presents for firms. By the end of this module, you’ll be able to better navigate the risks of AI and construct a more efficient and successful AI strategy for your business.

Module Overview:

  • Interview with Apoorv Savena
  • AI-Driven Business Transformation
  • Developing a Portfolio for AI Projects
  • Lowering Barriers for AI Use
  • AI in the Organizational Structure
  • Risks with AI
  • Governance
  • Course Takeaways

Why Study Artificial Intelligence in Business?

  • 71% of organizations and leaders perceive AI and Machine Learning are “game-changers”1
  • 78% of brands have already or are planning to implement AI by 20202
  • Growth of the global AI market is forecast to grow to $118.6 billion by 20253

1 Sources: MemSQL, Accenture,,,

World-Class Wharton Faculty

Wharton’s outstanding faculty have worked for and consulted to large multinationals, health care and biopharma organizations, public and not-for-profit corporation, and small entrepreneurial organizations.

Kartik Hosanagar photo

Kartik Hosanagar

John C. Hower Professor
Professor of Operations, Information and Decisions

Faculty research interests

  • Internet advertising
  • E-commerce
  • Digital media
  • Technology enablers
  • Data infrastructure
  • Personalization technologie

Kartik Hosanagar is the John C. Hower Professor of Technology and Digital Business and a Professor of Marketing at The Wharton School of the University of Pennsylvania. Kartik’s research work focuses on the digital economy, in particular the impact of analytics and algorithms on consumers and society, Internet media, Internet marketing and e-commerce.

Let us help you reach your full potential