45-884 AI Methods for Social and Visual Data
6 units, Carnegie Mellon University
AI Methods for Social and Visual Data prepares MBA and master's-level students to harness the power of modern artificial intelligence for analyzing unstructured data such as text, images, and multi-modal content. The course focuses on the practical use of foundation models such as GPT-5, Gemini, and Claude to tackle business-relevant problems in domains like customer experience, brand management, marketing, and operations. Students will learn how to interpret and apply the outputs of large-scale AI models without needing to build or train them from scratch. The course is structured around real-world cases, hands-on labs, and guided assignments that introduce cloud-based tools from platforms like Google Cloud. Students will use these tools to analyze customer reviews, social media images, marketing content, and other forms of unstructured data. Emphasis is placed on prompt engineering, multi-step workflows, visualization of model outputs, and the communication of actionable insights. Assignments are designed to help students build practical AI literacy without requiring deep coding or prior experience with machine learning. In addition to technical fluency, the course explores ethical, strategic, and organizational considerations associated with deploying AI systems in the real world. Topics include model bias, interpretability, the role of human oversight, and discussions of emerging legal frameworks. By the end of the course, students will be equipped to evaluate AI opportunities, understand foundational AI technologies, and participate meaningfully in the design and implementation of AI-enabled business solutions.
Prerequisites: none listed
Offered: Fall 2026, Summer 2026, Fall 2025
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