Masters Courses 7
Graduate courses at Carnegie Mellon Heinz College, taught across the MAISM, MISM, and MPPM programs.
Fundamentals of Operationalizing AI
Artificial Intelligence and Generative AI are increasingly easy to prototype but still hard to scale into reliable, repeatable business value. The biggest barriers are rarely the modeling algorithms themselves. In one large survey, 74% of organizations reported struggling to achieve and scale value from AI, with challenges driven primarily by people and process factors.
AI Model Development
Large Language Models are reshaping how we reason, generate structured outputs, and build intelligent systems. At the core of these capabilities are transformer-based architectures and scalable pipelines for adapting, evaluating, and deploying models in production. AI Model Development is a rigorous, hands-on course that teaches students how to design, refine, and operationalize LLM-based systems across diverse real-world applications.
Applications of NL(X) and LLM Systems
Large language models are reshaping how we interact with information, automate reasoning, and build intelligent applications. This course provides a rigorous, hands-on introduction to the scientific principles, engineering practices, and applied design of LLM systems, preparing students to build and evaluate real-world solutions.
Responsible AI — Principles, Policies, and Practices
As artificial intelligence technologies advance, so do the complexities and risks that organizations must govern. Responsible AI: Principles, Policies, and Practices prepares executives to systematically manage AI risks, operationalize ethical principles, and lead robust governance strategies across traditional, Generative, and Agentic AI systems.
Agent-Based Modeling and Agentic Technologies
Agentic AI is transforming industries, from autonomous decision-making in finance to intelligent policy simulations and gaming AI. With rapid advances in LLM-powered agents, multi-agent collaboration, and AI-driven simulations, agentic technology is now one of the most dynamic areas of research and investment. This course bridges the gap between traditional agent-based modeling (ABM) and modern agentic AI, equipping students with both foundational principles and cutting-edge techniques for building autonomous, decision-making AI systems.
Agent-Based Modeling and Agentic Technologies
This course examines the evolution from classic agent-based modeling to modern agentic technologies. Students begin with complex adaptive systems, emergent behavior, programmed behavior, and simulation tools, then move into LLM-based agents that perceive, reason, remember, use tools, coordinate with other agents, and act in digital or physical environments.
Agent-Based Modeling and Digital Twins
The ability to model and simulate complex systems is paramount in the rapidly evolving landscape of technology and data science. The growth of Large Language Models is resulting in generative agents that combine the capabilities of LLMs with reasoning, planning, and traditional AI to further advance the discipline of single-agent and multi-agent systems. This course offers a comprehensive deep dive into systems thinking, enabling students to discern when and how to deploy agent-based simulations and digital twins as effective solutions.
Online Certificate Courses 2
Certificate courses for working executives, delivered fully online over a multi-week term.
Operationalizing AI Systems
Artificial Intelligence and Generative AI are revolutionizing industries by enhancing efficiency, decision-making, and innovation. Yet nearly 75% of organizations struggle to achieve and scale value from AI initiatives, with approximately 70% of challenges stemming from people and process issues rather than algorithms. This course equips mid-level executives with the knowledge and tools to navigate these challenges effectively.
Responsible AI — Principles, Policies, and Practices
As artificial intelligence technologies advance, so do the complexities and risks that organizations must govern. Responsible AI: Principles, Policies, and Practices prepares executives to systematically manage AI risks, operationalize ethical principles, and lead robust governance strategies across traditional, Generative, and Agentic AI systems.
Executive Education 7
Short-form modules taught inside CMU executive and leadership certificate programs.
Agentic AI Foundations
Agentic AI Foundations is a four-hour module within the CMU Heinz College Chief Data and AI Officer Certificate Program. Agentic AI marks a categorical shift from generative AI, moving from systems that answer to systems that perceive, decide, and act, and this module gives data and AI leaders the conceptual foundation and executive vocabulary to direct it with confidence and cut through vendor claims.
Deploying and Monitoring AI Systems
Deploying and Monitoring AI Systems is a four-hour module within the CMU Heinz College Chief Data and AI Officer Certificate Program, marking the transition from the conceptual phase of data science to the practicalities of enterprise-wide AI application. It underscores the shift in focus from creating accurate models to deploying AI systems that are robust, secure, and operationally efficient, and it treats an AI system as far more than an AI model, requiring the convergence of data, models, and code.
Responsible AI Governance
Responsible AI Governance is a four-hour module within the CMU Heinz College Chief Data and AI Officer Certificate Program. As the world rapidly embraces artificial intelligence, the potential for both benefit and harm escalates, and this module navigates the complexities of responsible AI use with a detailed and practical understanding of the key risks and harms that traditional and generative AI can pose, the principles guiding ethical use, and how these harms manifest across the AI lifecycle.
Agentic AI Foundations
Agentic AI Foundations is the opening module of the DoD CDAIO Leading Agentic AI Certificate Program, a four-module executive program delivered by CMU Heinz College for defense data and AI leaders. Agentic AI is changing how organizations make decisions and solve complex problems, from autonomous operations to simulations for policy and training, and this module gives leaders the conceptual foundation to direct it with confidence.
Operationalizing AI
Operationalizing AI is a two-hour module within the CMU Heinz College CIO Program. Most AI value is lost not in building models but in turning them into systems that run reliably in production, and this module gives technology leaders a shared framework for scaling AI models into AI systems that deliver financial and strategic impact across predictive and generative AI.
AI - Risks, Principles, Policies, Governance
AI - Risks, Principles, Policies, Governance is a two-hour module within the CMU Heinz College Chief Risk Officer Program. AI risk is now a board-level agenda item, with binding law in force, an accelerating state patchwork, and incidents that carry direct liability, and this module gives risk executives the vocabulary, frameworks, and ownership model to govern AI across predictive, generative, and agentic systems.
Operationalizing AI
Operationalizing AI is a four-hour module within the Data Driven Leadership executive certificate, designed to help leaders move beyond isolated AI models toward production AI systems that deliver sustained mission and business value. It introduces a practical framework spanning strategy, value, operations, technology, responsibility, people, and culture, and grounds each idea in real deployment examples from defense and industry.