東北大學

Humankind is on the threshold of a new era—an age of artificial intelligence (AI) as revolutionary in its global impact as the Industrial Revolution. With the proliferation of machine learning and AI across all sectors of the global society, and fields such as financial services, healthcare, and robotics, GEOINT and cybersecurity are already changing as intelligent computers take on once-indispensably human tasks. There is an immediate need for individuals to be knowledgeable in how to manage, analyze, communicate, visualize, and lead in the area of AI by being data, technology, and human literate. The experiential AI curricula includes an introductory core, as well as an advanced core with an end-to-end AI education in the areas of finance, HR, business ventures, and healthcare/pharmaceuticals. The goal is to proactively and thoughtfully prepare students for the evolving technology and the challenges it presents. The curricula framework adopts a multidisciplinary approach to problem solving by combining computer science and analytical skills with functional government and industry expertise, creativity, and leadership with program offerings on-ground and online.

The degree program is distinguished from others by:

Focusing on the specific but widespread field of AI that exists within a variety of industries and applications

Northeastern faculty experts, who have extensive and proven experience in computer science, analytics, geospatial science, information technology, etc.

Courses that focus on providing critical skills in data management, data analysis, data visualization, problem solving, and advanced analytical tools, creating AI-driven decision making in fields like healthcare/pharmaceuticals, finance, HR, and business ventures

The learning outcome of our program focuses on providing students with both technical skills and design expertise:

Investigate and identify opportunities to address applications of AI and machine learning in the world to answer or solve an organizational question or problem

Articulate and defend the significance and implications of the intersection of technology and application in the context of AI and machine learning across multiple industries and organizations

Integrate the principles, tools, and methods of AI and machine learning to solve an organizational problem by making informed decisions related to the design and deployment of systems in human environments and workflows within the organization

Develop a formally proposed solution and/or application, real or hypothetical, to address an AI and machine learning related to privacy and ethical dilemmas that may be complicated by competing political, social, economic, or environmental interests

Apply data management and strategic analysis, problem solving, decision making, effective visualization/communication, and leadership skills to the application or deployment of machine learning and AI technologies and products in a real-world scenario