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The Data Science and Artificial Intelligence Program prepares visionary leaders to shape a better world in the digital age. Our mission is to educate deep thinkers and future builders who will drive societal progress through innovation and responsible technology. Throughout history, industrial revolutions have transformed society by harnessing technology and scientific breakthroughs—today's fourth industrial revolution is defined by seamless connectivity and artificial intelligence, reshaping industries and empowering communities. Data science and AI serve as the "brain" of this transformation, steering growth across every sector.
Beyond technical mastery, our program emphasizes a thoughtful understanding of technology's impact on society, encouraging students to become not only skilled professionals but also ethical leaders. We believe in balancing technical expertise with philosophical insight, ensuring that our graduates help create a more inclusive and people-focused world.
Upon completion of our program, students should be able to develop the following key capabilities:
Foundational Knowledge
Attain comprehensive foundational knowledge of the principles and applications of AI and data science.
Technical Expertise
Develop advanced technical expertise to design and implement technology-empowered, user-centric solutions.
Hands-on Experience
Enhance core competencies through hands-on learning, including real-world projects, internships, and civic initiatives across five global campuses, culminating in a comprehensive capstone project.
Design Thinking
Cultivate creative and convergent thinking abilities to identify and solve complex challenges in business, healthcare, education, and the social sciences using a design thinking approach.
Leadership Readiness
Prepare for leadership in a rapidly evolving field by gaining experience through research and collaboration with industry and academic partners.
Societal Impact
Understand the societal impact of technology, balancing technical mastery with ethical insight and philosophical reflection for responsible innovation.
Category
Courses
Fundamentals:
Exploring Data and AI Domain
DA200 Design of AI and Data-driven Services
DA201 Computational Thinking and Data Literacy
DA203 Database Design and Management: Exploring Data Ecosystems from Conceptual Models to Practical Applications
XD231 Experimental Design and Statistics: Scientific Inquiry & Methodology
Advanced:
Expanding Data and AI Mastery
DA311 Computational Decision Science: Bridging Analytics with Human Judgment
DA321 Data Analytics & Visualization for Social, Scientific, and Business Applications
DA322 Predictive Analytics and Modeling in Practice
DA331 Practical Applications of Machine Learning
DA332 Vision AI: Detection, Recognition, and Generation of Visual Information
DA411 Computational Mathematics for Diverse Applications from Science to Industry
Interdisciplinary:
Bridging Data Science and AI Across Domains
XD431 Next Generation AI: Linguistic, Agentic, and Generative AI
XD432 AI in the Real World: Use Cases in Society and Business
XD433 Affective Computing and Human-Robot Interaction
XD434 Creative Coding: Algorithmic Art and Design
XD401 Navigating Tomorrow: Emerging Technologies and Future Society
XD411 Special Cross-disciplinary Seminar I
XD412 Special Cross-disciplinary Seminar II
XD321 Data-Driven Discovery Across the Sciences
XD421 Science, Ethics, and Policy for Environmental and Urban Challenges
DA200 Design of AI and Data-driven Services
In this course, students learn to create human-centered service systems using data science and artificial intelligence. The course emphasizes hands-on learning and critical reflection, encouraging teamwork on real-world projects so that students can build practical skills in applying AI and data-driven solutions.
DA201 Computational Thinking and Data Literacy
In this course, students develop computational problem-solving and data literacy skills through hands-on projects, collaborative learning, and real-world applications. The course emphasizes structured thinking, data-driven insights, and effective communication, preparing students for data-centric fields.
DA203 Database Design and Management: Exploring Data Ecosystems from Conceptual Models to Practical Applications
This foundational course immerses students in data ecosystem, from modeling to real-world applications. Through pre-class lectures distilled to the essentials and hands-on in-class activities, students develop skills in database design, SQL, and data governance, preparing for careers in data science and analytics in today's digital ecosystem.
XD231 Experimental Design and Statistics: Scientific Inquiry & Methodology
This course introduces experimental design and statistical analysis for data science and AI. Students develop practical skills in research planning, data analysis, and ethical considerations through hands-on, collaborative projects, preparing them to conduct rigorous, impactful research.
DA311 Computational Decision Science: Bridging Analytics with Human Judgment
This course equips students with mathematical and computational tools for decision-making under uncertainty, blending theory with real-world applications. Through hands-on projects and Python-based simulations, students develop skills in advanced analytics, data-informed decision-making, and sensitivity to human factors—preparing for complex, data-driven environments.
DA321 Data Analytics & Visualization for Social, Scientific, and Business Applications
This advanced course equips students with skills in data analytics and visualization to solve complex challenges in social, scientific, and business domains. Students learn advanced analytical methods and visual communication, applying hands-on projects to interpret data and communicate insights responsibly.
DA322 Predictive Analytics and Modeling in Practice
This course empowers students to transform data into actionable intelligence for real-world challenges through hands-on machine learning and predictive analytics projects. Through real-world projects and case studies in business, healthcare, finance, and tech, students learn to build, validate, and deploy predictive models.
DA331 Practical Applications of Machine Learning
This course helps students unlock the power of AI to solve real-world problems with hands-on projects in machine learning and deep learning. Students gain practical skills in supervised and unsupervised learning, neural networks, NLP, and ethics, empowering them to design and evaluate impactful AI solutions for complex challenges.
DA332 Vision AI: Detection, Recognition, and Generation of Visual Information
Through this course, students will learn to unlock the transformative potential of Vision AI by bridging human perception with cutting-edge computer vision technologies. Through hands-on projects in healthcare, robotics, autonomous vehicles, and creative industries, students master deep learning, image analysis, and ethical considerations—empowering them to design, implement, and critically assess impactful visual AI solutions for real-world challenges.
DA411 Computational Mathematics for Diverse Applications from Science to Industry
This course empowers students to tackle real-world challenges in science, engineering, and business domains by applying computational mathematics, preparing students to excel in diverse professional and research settings. Through hands-on projects and case studies, students learn to model complex problems, develop robust computational solutions, and communicate results.
XD431 Next Generation AI: Linguistic, Agentic, and Generative AI
This course introduces next-generation AI, focusing on advanced language intelligence, agentic AI, and generative models. Students gain hands-on experience building autonomous, creative AI systems, with ethical considerations and real-world applications across business, science, healthcare, education, and creative industries.
XD432 AI in the Real World: Use Cases in Society and Business
This course explores the transformative impact of artificial intelligence across society, business, science, and engineering. Students build practical skills in AI concepts and technologies, apply them to real-world challenges in healthcare, finance, industry, and more, and critically examine the ethical and societal implications of AI adoption.
XD433 Affective Computing and Human-Robot Interaction
This course introduces affective computing and human-robot interaction, focusing on how emotional intelligence and robotics intersect. Students gain hands-on experience in emotion analysis, interface design, and real-world applications in social, healthcare, and business settings, while critically examining ethical and societal implications.
XD434 Creative Coding: Algorithmic Art and Design
This course explores coding as a creative medium for artistic expression and visual design. Through hands-on projects and critical discussion, students develop practical skills in creative coding, algorithmic art, and collaborative remixing—building a portfolio of original digital artworks and a strong foundation in coding for creative inquiry.