Dual Master of Science-MBA in Applied Artificial Intelligence

The dual Master of Science-MBA in Applied Artificial Intelligence degree is designed for students that seek to have a deep technical knowledge in applied artificial intelligence as well as strong management skills and qualifications. This joint degree will give students strong business management skills to complement their engineering degree, accelerating their growth into management positions and opening a more diverse selection of career choices. The students will earn two separate master’s degrees at completion of this dual degree program.

This dual program offers an exceptional combination of management skills with deep and practical knowledge of the technical aspects of applied artificial intelligence engineering. The MBA program is particularly suited for engineers, as it incorporates a unique blend of courses on management skills, technology and analytics skills, and human skills.

Concentrations

Business Operations for Applied Artificial Intelligence

Program Objectives

The program prepares students to:

develop a strong background in understanding the theoretical foundations of artificial intelligence and deep learning.
understand a variety of engineering applications for AI, including intelligent communication networks, autonomous robotics, image processing and computer vision, embedded systems, smart Internet of Things, smart health, information systems security, biomedical engineering, financial engineering, transportation engineering, data engineering, and software engineering.
perform independent research in the applied AI field.
become managers/leaders in engineering firms or engineering departments of any firm.
establish new ventures and startups with expertise in engineering and the skills to start a business.

Program Outcomes

By the time of graduation, students will be able to:

apply knowledge in mathematics, computational science and physics to solve problems in artificial intelligence.
analyze real-world data inputs and information systems using engineering principles and modeling approaches.
design experiments and analyze results to determine process parameters, and to identify issues and methods for algorithm design and system analysis.
use mathematical, modeling, and engineering principles to design artificial intelligent algorithms and systems; be able to incorporate considerations such as feasibility, applicability, cost, legal/regulatory, societal impacts, etc. in designs.
use computer software for data acquisition, modeling, simulation, visualization and intelligent system design.
write and present polished technical reports at a level expected of the engineering profession, and be able to critically evaluate the technical literature and use it to obtain solutions to artificial intelligence and data engineering problems;
acquire in depth technical and managerial skills to be able to be effective leaders in technology companies in their field of study .
develop basic skills of management as well as gain knowledge of analytical methods for approaching organization problems.
integrate managerial and technical aspects of computer engineering.
demonstrate fluency in the current body of knowledge in computer engineering and apply that knowledge toward optimal decision-making process in their respective field of practice.
exhibit proper use of integrative thinking in order to holistically analyze the relationship between human activity and the natural, social, and economic environments.
acquire both qualitative and quantitative analytical skills and apply those skills in solving problems in the context of their professional interests and expertise.
possess high quality written and oral communication skills to efficiently communicate complex issues to a varied audience.
demonstrate a high level of professionalism and proper understanding of ethical boundaries in all undertakings.

Degree requirements

The program is a 57-credit degree program. Students are required to complete:

1 mathematical foundation course from the Master of Engineering degree program (3 credits)
4 core courses from the Master of Engineering degree program (12 credits)
3 credits project course plus 3 credit electives + 0 credit research seminar course or 6 credit thesis research (6 credits)
3 concentration courses in Business Operations for AAI (9 credits)
Additional 9 courses from MBA degree program (27 credits)

Mathematical Foundation Courses

Students are required to select one mathematical foundation course from the list below:

EE 602	Analytical Methods in Electrical Engineering	3
	Or
EE 605	Probability and Stochastic Processes I	3

Core Courses

Students are required to select four core courses from the list below:

AAI 627	Data Acquisition, Modeling and Analysis: Big Data Analytics	3
AAI 628	Data Acquisition, Modeling and Analysis: Deep Learning	3
AAI 646	Pattern Recognition and Classification	3
AAI 672	Applied Game Theory and Evolutionary Algorithms	3
AAI 595	Applied Machine Learning	3
EE 608	Applied Modeling and Optimization	3

Business Operations for AAI Concentration (required)

Select three courses from the list

BIA 500	Business Analytics: Data, Models & Decisions	3
BIA 610	Applied Analytics	3
MGT 657	Operations Management	3

Project or Thesis

Students in the Master of Science program are required to complete:

Project Track: 3 credit project course (800 course) and a 3 credit elective course at the 500 or 600 level. Students who enroll in the 3 credit project course (800 course) are required to enroll in the 0-credit co-requisite research seminar course, EE 820. The 3 credit elective course can be any graduate level course at the 500 or 600 levels within the Department of Electrical and Computer Engineering. Elective courses that are taken outside of the department require approval by the faculty advisor.

Thesis Track: 6 credit thesis course (900 course). Students need to take the first 3 credit thesis course (900 course) in the third semester and the second 3 credit thesis course (900 course) in the fourth semester.

Requirements for MBA degree (with ECE concentration) in the dual degree program

MGT 606	Economics for Managers	3
FIN 623	Financial Management	3
MGT 612	Leader Development	3
MGT 635	Managerial Judgment and Decision-Making	3
MGT 641	Marketing Management	3
MGT 663	Discovering and Exploiting Entrepreneurial Opportunities	3
MGT 699	Strategic Management	3
MGT 810	Special Topics in Management	3 - 60
FIN 523	Financial Management	3