Course Overview

Generative AI (GenAI) stands at the forefront of a technological revolution, poised to redefine how businesses operate and deliver value. This course delves into critical questions at the heart of this transformation: How will GenAI reshape modern enterprise? What strategies should businesses adopt to integrate this technology effectively? How can existing data be leveraged to unlock new opportunities? What are the ethical and regulatory issues to consider?

These questions are pivotal whether you aspire to be a corporate innovator driving AI initiatives or a startup founder focused on the burgeoning GenAI market. Understanding the complexities of GenAI goes beyond using ChatGPT-type applications and prompt engineering. It requires immersive engagement in the technology, putting oneself in the decision-maker's shoes, and grappling with how GenAI can solve business challenges and opportunities.

This course offers an active learning environment where you will explore these questions through hands-on experience, directly linking conceptual understanding to business use cases. Whether you are a GenAI novice or possess some technical knowledge, this course is designed to enrich your understanding and prepare you for leadership in the GenAI-driven business landscape. You don’t need to know coding to take this class.

(Given the rapid pace of change in the Gen AI space, the course content listed below is subject to change.)

Educational Objectives

This new half-course is specifically designed to immerse you in the world of enterprise GenAI through a hands-on, project-based approach. This course is tailored for students of all technical backgrounds, ensuring that everyone, from those without prior AI experience and those that are experts, can all deeply engage with the material and project work.

The course will tackle real-world business use cases of Gen AI and each week’s content has been designed to build progressively on knowledge and skills. This approach not only enhances your theoretical understanding but also equips you with practical tools to apply in real business scenarios.

As you navigate through the course, engaging with guest protagonists and delving into hands-on projects, you will develop a comprehensive understanding of the key stakeholders and technical dynamics involved in GenAI enterprise applications. While the projects are closely aligned with real-life scenarios, they have been adapted to align with our teaching agenda and fit within the course format.

Course Structure

Each week of the course covers a module with three components:

• Pre-class: You will engage with a curated selection of readings and videos, serving as the foundational knowledge base for each week.

• Class session: In class, you will connect the dots among the various concepts introduced in the pre-class phase. We will also have guest protagonists, who bring their experience in creating Gen AI products or in enterprise Gen AI implementation into the classroom, grounding your learning in practical contexts.

• Post-class: Apply weekly learnings to team projects, blending theory with practical implementation. These activities are essential for consolidating your understanding and applying GenAI concepts in realistic business scenarios.

Course will be graded based on class-participation, interim deliverables, and the course project.

Course Content

The overall list of topics we will cover in the six-week schedule is as follows:

• Introduction to Generative AI

  Deep dive into the world of GenAI, understanding its fundamental principles and distinguishing it from other AI technologies. How are generative models different from other predictive AI techniques and why does that matter for business applications? We will explore what types of use cases are more suitable for generative solutions or other AI methods. Understanding the transformative potential of GPTs in the business landscape will set the stage for you to develop GenAI-driven business solutions.

• Adopting GenAI in Enterprises, Business Models, and Monetization

  Through real-world case studies, gain insights into how businesses are currently utilizing GenAI. Gen AI can be applied for better efficiency in existing processes or more interestingly to create new sources of value and new business models. How are early adopters finding functional uses (as in product management, finance, marketing, sales, supply chain, etc.) as well as industry use cases (e.g., healthcare, insurance, etc.). You'll identify key stakeholders and enablers and challenges in integrating GenAI into business operations including impact on workforce and human capital.

• Model Selection and Data Strategy for Enterprise GenAI

  How do we select the right Gen AI model? How do we get the data systems organized for Gen application development and implementation? We’ll focus on the critical role of models and data in GenAI applications. You'll delve into strategies for data preparation, understanding the GenAI data lifecycle, and formulating ethical and effective data management strategies.

• Ethical Implications and Regulatory Landscape of GenAI

  Address the ethical considerations and regulatory frameworks surrounding GenAI. You will explore the challenges of privacy, copyright, and compliance in GenAI applications, developing a nuanced understanding of how to navigate these issues. You will learn to assess the risks associated with Generative AI, propose mitigation techniques, and adapt business models to comply with ethical and regulatory standards.

• The Business Impact of GenAI

  Learn how to define and measure the success of GenAI initiatives. How do we think about AI with and without human augmentation? This week emphasizes understanding the broader implications of GenAI on company performance, equipping you with the tools to analyze and articulate the business impact of GenAI projects. We will examine how to define impact metrics and how to set up quantifiable success metrics for different types of GenAI projects.

• Scaling & Optimization

  Prepare for the challenges of scaling GenAI solutions. Gain insights into cost dynamics, infrastructure selection, and performance optimization. You’ll also learn about choice of platforms and other technical aspects of scalability.

• Course Group Project

  The course will involve hands-on group projects across various industries and business domains. These projects are intended to introduce students to the current state of the art technology and build practical skills that are needed for Gen AI implementation.

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