NBAY 6920

NBAY 6920

Course information provided by the Courses of Study 2024-2025.

The purpose of this class is to introduce you to fundamental concepts in data science & machine learning (ML) and prepare you for your career path as an entrepreneur or various business roles (e.g. product manager, marketing, operations, consulting…etc) in for-profit & non-profit organizations. This course differs from the classes offered from the engineer side in that we will use a business-centric approach, where we first begin with the business problem to be solved, and then we cover the technical methodologies to solve the context-specific use cases. Throughout the course I will teach you a decision-making framework to unite the various disparate use cases under a common thread. This framework draws upon my years of experience as both an AI researcher and as a business consultant. I have been fortunate to apply ML to various business contexts, from Silicon Valley startups to the Fortune 500, from private equity to non-profit organizations, and I am actively using and evolving this framework in my current role as an entrepreneur in my own AI startup. I will show you how to use this framework using a mixture of business case studies, real-world context data sets, lectures, and guest speakers. My hope is that you will leave this course with the skills to assemble the talent/resources to tackle the data science and ML challenges that you will encounter when you work for large firms or starting your ventures.

When Offered Spring.

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Syllabi: none
  •   Seven Week - Second. 

  • 1.5 Credits GradeNoAud

  • 12309 NBAY 6920   LEC 001

    • T
    • Mar 18 - May 6, 2025
    • Lee, C

  • Instruction Mode: In Person
    Enrollment limited to: Cornell Tech Master of Business Administration (MBA) students. This class is open to Non-MBA students who have completed TECHIE 5310 - Business Fundamentals (or received a waiver). Enrollment via waitlist will also be considered. This course counts as a Management Science Elective.
    Add/Drop dates: 9:00am, March 12, 2025 – 11:59pm March 19, 2025. If you drop after April 9, 2025, you will also receive a "W" on your transcript.