Office: Interdisciplinary Science Building 850

Telephone: 408-924-2735

Email: applied-data-science@sjsu.edu

Professors

Lee C. Chang
Simon Shim, Chair

Assistant Professors

Shih Yu Chang
Taehee Jeong
Guannan Liu
​Mohammad Masum
Vishnu Pendyala

Overview

The Applied Data Science Department offers academic programs to address the emerging workforce demands of interdisciplinary talent by designing and deploying intelligent solutions in order to address real-world data challenges.  Students gain a comprehensive understanding of the principles, methodologies, and technologies of applied data science and artificial intelligence (AI), including generative AI (GenAI).

Located in Silicon Valley, known for its leadership in big data and AI innovation, our programs align closely with industry needs. Employers increasingly seek professionals who can build, evaluate, and deploy AI systems and AI-assisted decision-making workflows as data continues to expand in scale and complexity. The department continuously seeks guidance from leading data professionals and companies to ensure the curriculum remains relevant to Silicon Valley workforce needs. The curriculum is aligned with an AI-forward market, where roles increasingly emphasize GenAI and AI-and-data skill sets.

Local data professionals regularly interact and engage with our students through teaching classes, delivering seminars, sponsoring internships, and supervising master’s projects that increasingly incorporate AI-driven tools, automation, and agentic workflows.  Faculty actively engage with industry partners to assess the curriculum and update learning objectives. This ensures students develop up-to-date skills that support regional innovation, including AI-enabled agents, intelligent systems, and responsible AI practices.

The department serves as an academic hub, in partnership with other SJSU departments and industry partners, for promoting education and research in applied data science and AI. The MS in Applied Data Intelligence program is designed to meet growing demand for AI- and applied data science professionals. It provides advanced training in order to draw insights from real data and apply AI skills to solve practical problems. This prepares graduates for evolving industry roles that emphasize AI capabilities and data-centric practices.

Programs

• Applied Data Intelligence, MS

Courses

• DATA 200 - Computational Programming for Applied Data Intelligence
• DATA 201 - Database Technologies for Applied Data Intelligence
• DATA 202 - Mathematics for Applied Data Intelligence
• DATA 220 - Advanced Mathematical Methods for Data Intelligence
• DATA 225 - Database Systems and Management for Data Intelligence
• DATA 226 - Big Data and Data Warehousing
• DATA 228 - Big Data Technologies and Applications for Data Intelligence
• DATA 230 - Data Intelligence and Visualization
• DATA 236 - Distributed Systems for Data Engineering
• DATA 240 - Data Mining Techniques and Applications for Data Intelligence
• DATA 245 - Machine Learning Technologies
• DATA 255 - Deep Learning and Computer Vision in Applied Data Intelligence
• DATA 260 - Agentic Artificial Intelligence and Distributed Systems
• DATA 262 - Embodied Artificial Intelligence Systems
• DATA 265 - Large Language Models Applications
• DATA 266 - Generative Artificial Intelligence and Large Language Models in Applied Data Intelligence
• DATA 270 - Data Intelligence Processes
• DATA 294 - Data Intelligence Seminar
• DATA 295 - Special Problems in Data Intelligence
• DATA 297 - Data Intelligence Internship
• DATA 298A - Master of Science in Applied Data Intelligence Project I
• DATA 298B - Master of Science in Applied Data Intelligence Project II
• DATA 299A - Master of Science in Applied Data Intelligence Thesis I
• DATA 299B - Master of Science in Applied Data Intelligence Thesis II
• DATA 1290R - Culminating Experience Supervision