Generative AI for Leaders

Generative AI for Leaders (TECH-650)

Description

This digitally delivered RPI ProCourse is crafted for current and aspiring business or technology leaders who want to leverage generative AI and large language models (LLMs) to drive transformative business outcomes. Through a combination of hands-on exercises and a capstone project, participants will gain a deep understanding of generative AI’s potential to enhance business operations, critically evaluate their organization’s readiness for AI, and develop a practical use case for AI integration. Upon completion, participants will receive a digital credential and a Certificate of Completion from RPI, underscoring their expertise in this transformative field.

Project Overview

In this course, you will embark on a structured journey through key concepts in generative AI. You will start with foundational topics like tokens, parameters, and model structures, and advance to practical applications such as fine-tuning, prompt engineering, and responsible AI adoption. In the first week, you will explore AI fundamentals and the transformative potential of large language models (LLMs), along with an initial assessment of your organization’s readiness. This assessment will help you identify where AI can add immediate value in your context and set the stage for targeted applications in later sessions.

As you progress, you will delve into solution architectures and develop skills to strategically apply generative AI across various scenarios. You will work on parameter-efficient fine-tuning, prompt engineering, and retrieval-augmented generation (RAG), gaining practical skills to enhance model accuracy and relevance for your specific business needs. You will learn to design effective prompts, optimize responses, and evaluate solution patterns that align with your organization’s operational framework. You will also focus on the cultural and technical prerequisites needed to support AI initiatives and explore the importance of organizational readiness for realizing AI’s full potential.

By the final week, you will have developed a tailored AI use case with a strong focus on managing ethical considerations, mitigating risks, and ensuring sustainable implementation. The program concludes with a pitch session, where you will present your AI strategy to peer executives and receive feedback on your approach. This course equips you with a solid understanding of generative AI’s strategic and operational impact, along with actionable frameworks and insights to champion AI-driven innovation responsibly and effectively within your organization.

Technology & Logistics

You will complete all coursework through Rensselaer’s digital classroom environment, with feedback provided by your course mentor along the way. The coursework will primarily be self-paced, with synchronous sessions that will provide an opportunity to engage with the content and course mentor(s) in a live setting.

Audience

This non-credit course is designed for current and aspiring business or technology leaders who seek to leverage generative AI and large language models (LLMs) to drive transformative business solutions. No prior education is required. 

Payment

Payment is accepted via credit card only. Refunds (minus processing fees) may be issued up to the course’s official start date. After the course has begun, refunds are no longer available. 

If you have any questions about the course prior to enrolling, please contact procourses@rpi.edu. 

Learning Goals

Course completion enables you to:

• Define generative AI and large language models (LLMs), identifying strengths, weaknesses, and differentiators from traditional analytic tools.
• Assess an organization’s readiness for generative AI or LLM adoption to address business issues.
• Articulate a use case for how generative AI and LLMs can address real-world problems within an organization.
• Select a generative AI or LLM solution for a given use case and create a benefit vs. complexity matrix to justify model selection.
• Develop strategies to foster an organizational culture that promotes responsible AI use through effective collaboration, communication, and accountability.
• Develop a pitch for organizational leaders that exemplifies an AI strategy for a given use case.