Generative AI using Python

Apply generative AI with Python for business and organizational impact

This pathway is designed for professionals with foundational Python skills who are ready to apply programming to generative AI development. This pathway builds proficiency for roles such as AI Business Data or Policy Professional, combining AI literacy, strategic insight, and hands-on experience designing AI-enabled applications. An elective allows learners to deepen skills in data analytics or explore the ethical and policy implications of AI in the workplace.

Students will complete these two 2.5-credit courses focused on AI in business (5 credits total)

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*Students can choose between these two courses

Core Curriculum
 

GBA 478: AI in Business

GBA478 covers the application of generative AI technologies across diverse business contexts, helping you understand how to integrate these tools into modern workflows. The course provides frameworks for deciding when and how to use generative AI effectively, along with hands-on experience designing AI tools that create business value and programming basic LLM-driven applications in Python. It also explores the broader implications of generative AI, encouraging you to engage with the moral, philosophical, and ethical questions surrounding these technologies.

GBA 479: Generative AI in Business Applications

This course focuses on the design and development of generative AI–enhanced business applications, with a framework for integrating Gen AI tools and capabilities into business processes, tasks, and workflows. Students learn to program with Gen AI tools and large language models using Python and APIs, build AI-driven systems that execute dynamic tasks, and develop multi-agent architectures for complex workflows. The course also explores Retrieval-Augmented Generation (RAG) to access private knowledge bases built on organizational data. By the end of the course, students will have the technical and conceptual skills to design and build generative AI applications tailored to modern business needs.

Students also choose an additional course from the two courses below (2.5 credits each):
 

GBA 473: Data-Driven Decision-Making

This course focuses on understanding the analytics environment, including organizational challenges, data, and the role of models, while applying frameworks for data-driven decision-making in business. It covers marketing, operational, and business analytics, with generative AI used throughout to enhance discovery and the articulation of ideas. Students also learn to apply analytics design concepts to decision-oriented projects and develop systematized dashboards to support organizational insights.

GBA 444: Ethics and Policy in Tech

This course explores the ethical and policy challenges facing tech firms, from start-ups navigating regulatory barriers to industry leaders addressing antitrust concerns. It examines the complex ethical questions surrounding AI and encourages students to think systematically about issues such as governance and the use of guardrails. Students develop skills to assess the policy and ethical environments of organizations and understand how these intersect with market dynamics, with tools applicable across industries.