Technology-Driven Entrepreneurs

Entrepreneurship is increasingly being empowered by technological innovations like AI and machine learning. While entrepreneurship has always entailed innovation and risk-taking, the increasing focus on fast-paced and disruptive innovation brings uncertainty and challenges facing current-day entrepreneurs to a new level.

PROGRAM OVERVIEW

Entrepreneurship is increasingly being empowered by technological innovations like AI and machine learning. While entrepreneurship has always entailed innovation and risk-taking, the increasing focus on fast paced and disruptive innovation brings the uncertainty and challenges faced by current-day entrepreneurs to a new level. This curriculum will help students face such challenge through building a solid theoretical foundation and obtaining the practical knowledge of technology-driven entrepreneurship, especially in the practical business implementation of AI and machine learning. The online course covers the history and evolution of technology-driven ventures, the characteristics and implications of disruptive technologies, the theory and practice of consumer-focused thinking, and the key features and trends of information-rich innovations. Combining these key aspects, students will develop and practice with framework for creating successful technology-driven businesses in AI and machine learning.

 

Completion

This thirty-hour mini online course (30.0 instructional hours) will be provided online during a three-week period of four-days per week. Each day will range from two to three hours of instruction, including 15-minute breaks between topics, totaling ten instructional hours per week.

Who should attend:

Entrepreneurs

Entrepreneurs who are involve in an AI or Machine Learning start-up project.

Executives

Executives who make business decisions and would like to bring the applications of innovations to current companies

Investors

Investors who are interested in the future of the innovation of AI and Machine Learning

Goals and Objectives

  • Theoretical and fundamental understanding of entrepreneurship

 

  • History and evolution of technology-driven firms

 

  • Characteristics and implications of disruptive technologies like AI and machine learning

 

  • Consumer-focused, information-driven opportunity-seeking

 

  • Application strategies and methods to recognize and seize innovation opportunities in a global and culturally diverse market

Program Curriculum

Module
1
Module
01
  • Day 1 and 2: History and Evolution of Technology-Driven Entrepreneurship (6.0 hours)

Day 1 and 2 lay the theoretical foundations of entrepreneurship, and reviews the history and development of technology-driven ventures over time, leading to the current industry landscape and the key success criteria wherein.

Module
2
Module
02
  • Day 3 and 4: Disruptive Technologies (6.0 hours)

Day 3 and 4 focus on the concept and the practice of disruptive technologies. Disruptive technologies and innovations will be compared with and contrasted to standard evolutionary innovations. Key business and economic implications of disruptive technologies, to firms of different size and market position, will be covered from both theoretical and practical perspectives.

Module
3
Module
03
  • Day 5 and 6: Consumer-Focused Value Creation (6.0 hours)

Day 5 and 6 focus on identifying value creation opportunities through analyzing consumers. Compared with the previous generation of technology firms which often focus on the back-end operations, the current generation of successful ventures typically focus on the front-end consumer interactions. A marketing perspective of developing a keen understanding of consumer needs and developing value creation initiatives to consumers, is the key to success in the current business landscape, and will be covered.

Module
4
Module
04
  • Day 7, 8, and 9: Information-Rich Innovation (6.0 hours)

Day 7, 8, and 9 focus on understanding the information aspect of technology-driven innovations. Most recent innovations in the technology domains have a heavy focus on information, in contrast to earlier innovations that typically focus on functional capabilities. The evolution, key characteristics, and business implications of information-rich innovations, as well as opportunity identification from this perspective, will be covered on day 7 and 8.

Module
5
Module
05
  • Day 10, 11, and 12: Creating Technology-Driven Ventures (6.0 hours)

Day 10, 11, and 12 synthesizes the key concepts covered in the previous four days of the course and develops an integrated framework for developing successful technology-driven ventures. Students work on a mini-project to practice with the framework and to consolidate the knowledge covered in the course.

Fee & Discount

  • Fee:$3,000 (includes course, student materials, select follow-up events)

 

ENROLLMENT REQUIREMENTS

Earned degree at BA level or above, or equivalent employment experience in business management and leadership position(s).

METHOD(S) OF INSTRUCTION

Online Classroom, including interactive lectures, discussions, and team group work.
Zoom will be the primary platform through which classes will be taught.

COURSE MATERIALS & EQUIPMENT

A course packet with a book (or books), as well as published articles, white papers, and case studies will be shipped or emailed to students before the course start.
A computer with Zoom installed.

 

New York State Education Department Info

New York State Education Department / Bureau of Proprietary School Supervision

Online Class Approval Status: Pending

Contact:
New York State Education Department / Bureau of Proprietary School Supervision
116 West 32nd Street, 5th Floor
New York, New York 10001
Telephone Number: (212) 643-4760
Facsimile Number: (212) 643-4765
http://www.acces.nysed.gov/

Selected Faculty

Henry Cao

Professor of Finance and Chair of Finance Department

PhDs, UCLA and Yale

Areas of Expertise:

Asset Pricing, Behavioral Finance, Cryptocurrencies, Hedge Funds and Alternative Investments, Microstructure, Options Pricing, International Finance
About

Dr. Cao earned a PhD in Finance in 1995 from UCLA and a PhD in Pathology in 1991 from Yale University. In 2016, he was on the list of “China’s Most Cited Researchers” unveiled by Elsevier, the world’s famous provider of scientific, technical, and medical information.

Before joining CKGSB, he taught at UC Berkeley, UCSD, Ohio State University, Carnegie Mellon and UNC Chapel Hill. Cao’s research has been published in journals including Journal of Finance, Review of Financial Studies, Journal of Financial Economics, Journal of Economic Theory, Journal of Business, Review of Finance and Marketing Science. Cao is the co-editor of International Financial Review and sits on the editorial board of Annals of Economics and Finance and China Financial Review. Cao has been speaking about blockchain technology globally, his speech topics include “A New Paradigm of Blockchain”, “The Parallel World on Blockchian” etc.

Baohong Sun

Dean's Distinguished Chair Professor of Marketing

Director of the CIM Center

Associate Dean for CKGSB Americas and Global Programs
 
PhD, University of Southern California

Areas of Expertise:

Big Data Marketing, Consumer Behavior and Trends, Customer Relationship Management, Digital Branding and Marketing, Dynamic Structural Models and Interactive Marketing Mix, E-commerce, Pricing Strategy, Social Commerce
About

Professor Sun Baohong is the Dean’s Distinguished Chair Professor of Marketing and the Associate Dean for CKGSB Americas. She also directs CKGSB’s Customer Information Management Center. Prior to joining CKGSB in 2011, Professor Sun was Carnegie Bosch Professor of Marketing at the Tepper School of Business of Carnegie Mellon University. Professor Sun received her PhD from the University of Southern California in 1997 and BA from Renmin University of China.

Liye Ma

Associate Professor

PhD, Carnegie Mellon University

Areas of Expertise:

Marketing
About

Joined the University of Maryland in 2011.

Liye Ma teaches the undergraduate Marketing Research Methods class and the Data Science class in the MS Marketing Analytics program. His research focuses on the dynamic interactions of firms and consumers on Internet, social media, and mobile platforms. His work has been published in various journals including Marketing Science, Journal of Marketing Research, Management Science, and Information Systems Research. He joined the Marketing Department in Fall 2011 after obtaining the Ph.D. degree from the Tepper School of Business at Carnegie Mellon University.

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Online Classroom Access

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