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Course Description

Overview

This course provides a practical, hands-on introduction to the world of Generative AI from a business perspective. You will learn how these AI skills are being applied today to automate marketing campaigns, develop new financial analysis tools, streamline supply chain operations, and create intelligent customer service solutions. In today's economy, understanding how to build with and manage AI is no longer a niche technical skill—it's a core business competency. This course moves beyond theory and buzzwords, treating you as a product manager and developer tasked with building a real-world AI application. While this is not a course for programming beginners, it is designed for business students with a foundational knowledge of Python. We will build upon the skills from the prerequisite courses, focusing on applying them rather than learning them from scratch.

A unique aspect of this course is our 'AI-assisted learning' approach. 🤖 We won't just study AI; we will use it as a creative partner and a productivity tool. You'll leverage AI for brainstorming project ideas, assisting with code development, and deepening your own research, learning the critical meta-skill of how to collaborate effectively with intelligent systems.

Through a semester-long, project-based experience, you will learn to identify business opportunities for AI, design user-centric applications, and build a functional AI-powered prototype using enterprise-grade cloud tools. This is an intensive, experiential course. Success requires continuous engagement, collaborative teamwork, and a curiosity to build with the defining technology of our time.

Learning Objectives

Upon successful completion of this course, you will be able to:

  • Identify & Strategize: Analyze business processes and identify high-value opportunities for applying Generative AI solutions.
  • Design & Plan: Translate a business idea into a formal product plan, complete with user personas, experience maps, and technical requirements, using professional project management tools like GitHub.
  • Build & Prototype: Develop a functional AI chatbot or application prototype by customizing and extending a foundational code scaffold.
  • Engineer Prompts: Design, test, and refine sophisticated prompts to control AI model behavior and ensure reliable, high-quality outputs.
  • Integrate Advanced AI Techniques: Implement advanced features like Retrieval-Augmented Generation (RAG) to allow your application to reason over specific documents and data.
  • Leverage Cloud Platforms: Use an enterprise-grade cloud platform (Google Cloud) to run and manage components of your AI application in a secure, sandboxed environment.
  • Collaborate with AI: Use AI-powered developer tools like CodeAssist as an effective coding partner to improve productivity and code quality.
  • Communicate & Demonstrate: Articulate the value, functionality, and ethical considerations of your AI application to both technical and non-technical audiences.