Applied AI Curriculum
Build Your AI Expertise. Shape Your Own Path.
The MS in Applied Artificial Intelligence is intentionally designed to balance shared foundations with individualized specialization. You’ll begin with a common core that develops advanced technical knowledge alongside the leadership and strategic thinking needed to implement AI responsibly. From there, you’ll customize your experience through five electives, building a portfolio that reflects your interests and the problems you want to solve.
Whether you’re interested in AI engineering, intelligent agents, enterprise AI, or industry-specific applications, you’ll graduate with practical experience applying AI across multiple domains.
Curriculum Details
The MS in Applied Artificial Intelligence is a 9-course program completed over three quarters, including 4 core courses and 5 electives.
Core Courses:
All students complete four core courses designed to develop advanced AI knowledge alongside the strategic, leadership, and governance perspectives needed to build and implement AI responsibly.
Elective Courses:
Students choose 5 electives from 8 options offered in the program’s inaugural year. Electives span the practical application of AI across industries, emerging AI systems and intelligent agents, and the infrastructure and technologies needed to build, deploy, and scale AI in real-world environments.
Electives are organized across three pillars, and students take at least one course from each. This structure provides breadth across applied AI while giving you the flexibility to go deeper in the areas that align with your interests and goals.
Use the interactive visualization below to see a sample course schedule for the program offerings.
- Sample Full-Time ScheduleQuarter 1 • 10 WeeksCore
- Artificial Intelligence I: Foundations and Principles Letter Grade
The AI systems behind applications such as recommendation engines, fraud detection, and intelligent search are built on a set of core techniques, and this course provides the foundation for understanding and applying them. Students develop fluency across machine learning, probabilistic reasoning, search, and optimization through practical use cases, spanning supervised, unsupervised, and semi-supervised approaches. The course develops both the intuition and technical depth to formulate and implement AI solutions from the ground up.
Core- Value Creation and Leadership with Artificial Intelligence Letter Grade
Artificial intelligence is forcing organizations to rethink how they compete, how work is designed, and how value is created . This course prepares leaders to move beyond experimentation to building AI-native organizations. Participants will learn to evaluate AI opportunities, redesign core workflows, align AI initiatives with business objectives, and lead the organizational change required as foundation models and autonomous agents reshape industries. The course emphasizes leadership, strategic adoption, responsible implementation, and Return-on-AI-Investment frameworks that distinguish meaningful transformation from technology theater.
Core- Artificial Intelligence Security, Safety, and Governance Letter Grade
The stakes of deploying AI responsibly have never been higher, from securing large language models against adversarial attacks to navigating emerging AI regulations. This course bridges the technical and governance dimensions of AI safety, covering model robustness, alignment strategies, risk assessment, and auditability alongside the ethical and societal considerations surrounding LLMs, autonomous agents, and multimodal systems. Students learn to evaluate vulnerabilities, design mitigation strategies, and build AI systems that are safe, transparent, and aligned with human values.
Quarter 2 • 10 WeeksCore- Artificial Intelligence II: Advanced Architectures and Applications Letter Grade
The most impactful AI systems today across various disciplines such as medical image analysis, robotics, and scientific discovery are built on a new generation of deep learning architectures. This advanced course covers architectures like CNNs, LSTMs, transformers, diffusion models, and GNNs alongside methodologies including transfer, reinforcement, causal, and contrastive learning, examining how these systems are trained, optimized, and deployed across real-world domains. The course moves from theory to state-of-the-art practice through hands-on experimentation and critical analysis of current research.
Elective- AAI Elective 1 Letter Grade
Elective offerings vary. Students will work with their academic advisor to select electives based on their interests and course availability. Past electives include:
Quantum Computation & Applications, Production AI in the Cloud, AI in Asset Management, Enterprise AI Systems, Agentic AI Ops, AI in Biomedicine, AI Innovation Practicum, and Multi-Modal Agents.
Elective- AAI Elective 2 Letter Grade
Elective offerings vary. Students will work with their academic advisor to select electives based on their interests and course availability. Past electives include:
Quantum Computation & Applications, Production AI in the Cloud, AI in Asset Management, Enterprise AI Systems, Agentic AI Ops, AI in Biomedicine, AI Innovation Practicum, and Multi-Modal Agents.
Quarter 3 • 10 WeeksElective- AAI Elective 3 Letter Grade
Elective offerings vary. Students will work with their academic advisor to select electives based on their interests and course availability. Past electives include:
Quantum Computation & Applications, Production AI in the Cloud, AI in Asset Management, Enterprise AI Systems, Agentic AI Ops, AI in Biomedicine, AI Innovation Practicum, and Multi-Modal Agents.
Elective- AAI Elective 4 Letter Grade
Elective offerings vary. Students will work with their academic advisor to select electives based on their interests and course availability. Past electives include:
Quantum Computation & Applications, Production AI in the Cloud, AI in Asset Management, Enterprise AI Systems, Agentic AI Ops, AI in Biomedicine, AI Innovation Practicum, and Multi-Modal Agents.
Elective- AAI Elective 5 Letter Grade
Elective offerings vary. Students will work with their academic advisor to select electives based on their interests and course availability. Past electives include:
Quantum Computation & Applications, Production AI in the Cloud, AI in Asset Management, Enterprise AI Systems, Agentic AI Ops, AI in Biomedicine, AI Innovation Practicum, and Multi-Modal Agents.
- Artificial Intelligence I: Foundations and Principles Letter Grade