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GenAI in Business: Planning Framework for Implementation

Offered By: University of Michigan via Coursera

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Generative AI Courses Business Strategy Courses Value Proposition Courses Data Integration Courses

Course Description

Overview

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In this course, you’ll learn how to identify the right business problems where generative AI can deliver the greatest value. We’ll guide you through the process of articulating these problems in terms of pain points and value levers, ensuring clarity for all stakeholders. Throughout each lesson, you’ll gain the main skills needed to “plan” your artificial intelligence acquisition, the second phase of the “See, Plan, Act” framework introduced in the “Generative AI in Business” series. With the problem defined, we’ll align it with the specific abilities your generative AI solution needs and help you choose the right technology and solution type. Finally, you’ll develop a three-step roadmap to organize your data, evaluate its quality and readiness, and select the best approach to integrate it into your AI solution. By the end of the course, you’ll have a detailed blueprint for your generative AI solution, a clear understanding of the data you need, and a strategy for integrating it effectively into your business. This is the second course in the “Generative AI in Business,” a course series for business professionals interested in using generative AI to support, enhance, and amplify the work of their organizations.

Syllabus

  • PAD Framework of GenAI Adoption: The Problem
    • In this module, we'll learn how to choose the right problem in your business for GenAI, and how to build a convincing case to key stakeholders on why the problem is worth solving.
  • PAD Framework of GenAI Adoption: The Ability
    • Now that you have a clear problem in mind, in this module you will learn how to identify the right GenAI solution types for that problem.
  • PAD Framework of GenAI Adoption: The Data
    • In this module, we’ll learn how to select the right data from your business and the most effective methods to integrate those data with your planned GenAI solution, in order to enable the solution to deliver the abilities that your problem calls for.

Taught by

Andrew Wu

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