AI For Business Specialization : A Free Course For Beginners

Introduction

This course is designed to teach you about machine learning, artificial intelligence (AI), and Big Data. The goal of this course is to provide you with the foundational knowledge needed to use these technologies in a variety of business settings.

In this course, you will also study the risks and ethical concerns of artificial intelligence (AI), discover how to create just governance structures and learn about the use of AI in marketing and people management. You will thoroughly grasp how artificial intelligence (AI) and Big Data are changing business procedures and improving consumer experiences through unique insights from pioneers in the field.

What Will You Gain from This Course

Following the completion of this course, participants will:

1. Gain a basic understanding of machine learning, artificial intelligence, and Big Data in a variety of commercial settings.
2. Evaluate the risks and ethical concerns related to the use of AI and provide frameworks for responsible governance.
3. Improve customer experiences and lifecycle management in marketing by implementing AI and machine learning techniques.
4. Utilize blockchain technology to enhance HR procedures and lessen bias by implementing AI tools and strategies.
5. Examine data-driven business strategies and use industry experts' ideas to tailor AI and Big Data to business change.

Skills Acquired:

1. Artificial Intelligence (AI)
2. Analytics
3. Machine Learning
4. Management
5. Fraud Prevention

Who Is This Course For

This course is designed for:

1. Experts in business who want to incorporate Big Data and AI into their plans.
2. HR directors who want to use AI to manage people more efficiently.
3. Marketing experts who are enthusiastic about leveraging AI to engage customers in a tailored way.
4. Technologists and data analysts seeking to comprehend the effective uses of AI in business.
5. Anyone curious about how ethical business practices and innovation can be fueled by AI and machine learning.

Course Content

4 Modules – 142 Videos – 15 Readings – 15 Quizzes – 3 Peer Reviews – 1 Assignment – Certificate of Completion

AI Fundamentals for Non-Data Scientists

This course explores machine learning for Big Data, including the development of algorithms using TensorFlow and Teachable Machine. You will learn how to improve algorithms and make use of the best training data as you learn ML techniques, Deep Learning, GANs, VAEs, and AutoML. The course includes interviews with executives from organizations such as Visa and McDonald's. It also covers error assessment, coding methods, no-code technologies, and data-driven business plans.

1. 33 Videos
2. 3 Readings
3. 3 Quizzes
4. 1 Peer Review
5. 1 Assignment

AI Applications in Marketing and Finance

This course explores the use of AI to improve targeted marketing, analyze consumer behavior, and enhance the customer experience and lifecycle. It uses supervised and unsupervised machine learning for fraud detection to handle credit risks, fraud, and consumer data security. With contributions from leaders in the fields of marketing, fraud prevention, and data analytics, the course offers a thorough grasp of how AI and machine learning affect consumer behavior and corporate objectives.

1. 29 Videos
2. 3 Readings
3. 4 Quizzes

AI Applications in People Management

This course examines machine learning and artificial intelligence in HR management, with an emphasis on data roles, AI applications, and leveraging blockchain technology to reduce prejudice. You will discover how to manage employees' lifespans, evaluate big data sets, and spot trends for business forecasts using cutting-edge technology. You will know how to use AI to optimize HR processes and how to use data for machine learning.

1. 38 Videos
2. 4 Readings
3. 4 Quizzes
4. 1 Peer Review

AI Strategy and Governance

This course explores AI strategies for corporate transformation and competitive advantage. You will gain knowledge about explainable AI goals and applications, corporate AI applications, and methods for reducing adoption hurdles. Developing appropriate AI governance algorithms, handling big datasets, and the application of AI to risk management and organizational transformation are all covered in the course. By the time you reach the end of the course, you'll be able to identify data biases, uphold user confidence, and create governance plans.

1. 34 Videos
2. 5 Readings
3. 4 Quizzes
4. 1 Peer Review

Description

With an emphasis on their real-world applications in many business fields, you will gain a comprehensive understanding of the fundamentals of Big Data, AI, and machine learning in this specialty. The curriculum helps the students recognize the hazards and ethical concerns related to artificial intelligence (AI) and discover how to create governance structures that guarantee ethical and responsible AI use.

The students will learn how to create equitable and efficient people management procedures and learn how AI might be incorporated into HR tasks. They will also learn how the customer journey and lifecycle may be improved and how data analytics and customization can propel marketing success. Finally, students will learn from experts in the field how Artificial Intelligence (AI) and Big Data are transforming business processes.

Upon completion of this specialty, you will possess the necessary skills to use ethical AI tactics, comprehend the relationship between AI, machine learning, and data analytics, and use these technologies to successfully shape and impact your company.

Meet the Instructor(s)

Michael R Roberts - University of Pennsylvania

Michael R Roberts is a professor of Finance at the Wharton School of the University of Pennsylvania. He has multiple teaching awards for undergraduates, MBAs, Ph. D.s, and executives.

Peter Cappelli - University of Pennsylvania

Peter Cappelli is a professor of Management at the Wharton School and Director of Wharton’s Center for Human Resources. He was named one of the top 5 most influential thinkers in management by the HR magazine and was elected as a fellow of the National Academy of Human Resources.

Raghu Iyengar - University of Pennsylvania

Raghu Iyengar is a professor of Marketing at the University of Pennsylvania. His research has been monumental in quality and quantity learning in learning models. His research has been well-received by the educational fraternity.

Prasanna Tambe - University of Pennsylvania

Prasanna Tambe is an associate professor of operations at the University of Pennsylvania. Currently, he teaches courses on AI applications in people management, AI strategy and governance, and AI fundamentals for non-data scientists.

Kartik Hosanagar - University of Pennsylvania

Kartik Hosanagar is a professor at the University of Pennsylvania. He has been recognized as one of the top 40 business professors under 40 in the world.

Kevin Werbach - University of Pennsylvania

Kevin Werbach is a professor of Legal Studies and Business Ethics at the Wharton School, University of Pennsylvania. He served on the Obama Administration’s Presidential Transition Team and also founded the Supernova Group.

Matthew Bidwell - University of Pennsylvania

Matthew Bidwell is the Associate Professor of Management at the University of Pennsylvania. He currently teaches courses on AI applications in people management, managing human capital in retail, and people analytics.

Lynn Wu - University of Pennsylvania

Lynn Wu is an Associate Professor at the Wharton School of the University of Pennsylvania. She teaches undergraduate, MBA, and PhD students about the impact of emerging technologies on business.