Master of Science in Data Analytics Engineering
Data is transforming the way organizations operate and make decisions. The increasing reliance on data-driven decision-making across industries has created a critical demand for professionals skilled in data analytics. As the UAE advances its strategic vision to become a global leader in artificial intelligence and digital transformation, the need for data analytics expertise is growing across key sectors, including supply chain, healthcare, manufacturing and government.
The AUS Master of Science in Data Analytics Engineering (MSDAE) program is designed for individuals seeking to develop and strengthen their analytical skills and managerial capabilities. The program helps students build a well-rounded skill set that supports thoughtful decision-making, problem solving and leadership in data-driven environments. Graduates are equipped to contribute to organizational improvement, lead data initiatives and guide digital transformation efforts. The program also provides a strong foundation for those who wish to pursue doctoral studies in data analytics engineering or related fields.
Offered through the Department of Industrial Engineering, the MSDAE benefits from experienced faculty, modern facilities and a curriculum that balances technical understanding with managerial relevance. The program emphasizes the ability to interpret data effectively, communicate insights with clarity and translate findings into actions that create measurable value.
The program equips students from diverse fields with the knowledge and skills needed to gather, organize, manage and analyze data, and—more importantly—how to apply these insights to support planning, operational enhancement and long-term strategic goals. Through applied projects, collaborative learning and exposure to real challenges, the program promotes practical understanding, professional growth and the ability to make informed decisions in complex settings. The MSDAE also contributes to the broader development of data analytics in the region by supporting research, innovation and the UAE’s ongoing digital transformation agenda.
Our program offers you the flexibility to choose one of two paths:
- Course-Only Option: Complete 10 courses
- Thesis Option: Complete 7 courses and a thesis
Mission Statement
The mission of the MSDAE program is to considerably increase the opportunities for practicing professionals to be successful in applying advanced data analytics engineering to drive informed decision-making, develop innovative engineering solutions, lead data-driven initiatives, and contribute to organizational growth and economic development for the private and public sectors of the UAE and gulf region countries.
Program Education Objectives
Graduates of the AUS MSDAE program will be prepared to:
- develop creative and effective engineered solutions through advanced analytical techniques
- contribute to industry and society with impactful, sustainable and intelligent solutions
- engage in research, continuous learning and emerging technologies
Program Outcomes
Upon graduation, an AUS MSDAE graduate should demonstrate the ability to:
- apply data analytics engineering techniques to solve complex problems involving large data from multiple sources
- use database management systems, data processing techniques, data visualization tools and data mining methodologies for effective data storage, retrieval and analysis
- design and develop data-driven solutions while considering public health, safety and welfare, and broader global, social, environmental and economic factors.
- demonstrate critical thinking and engineering-based problem-solving
- communicate data-driven insights effectively through technical presentations and reports
- perform theoretical and applied research projects
- demonstrate professional conduct and ethical responsibility in the practice of data analytics engineering
What are our admission and program requirements? What courses are taught in our program? Do students need to complete a master's thesis? The links and information below provide answers to these and other questions that you may have.
Admission Requirements
In addition to meeting the university’s general graduate admission requirements, applicants must hold a bachelor of science degree in engineering from an independently accredited university recognized by the UAE Ministry of Higher Education and Scientific Research and by AUS. Degreed individuals in fields closely related to engineering or other quantitative sciences may be considered on a case-by-case basis.
Requirements
Students in this program choose from two options: a thesis option and a non-thesis (course) option.
Accelerated Master’s Program—AUS Undergraduate Students
AUS undergraduate degree-seeking students interested in pursuing the MSDAE program may register for a maximum of six credit hours from MSDAE courses while completing their undergraduate degree program by seeking acceptance to the Accelerated Master’s Program (AMP) of the MSDAE program.
The master’s level courses may be counted towards meeting the graduation requirements for both the bachelor’s and master’s degrees.
To qualify for acceptance to the AMP, students must satisfy the following requirements at AMP application time:
- be enrolled in major offered by the College of Engineering
- have earned a minimum of 90 credit hours (excluding credit hours earned in Achievement Academy/Bridge Program courses and preparatory courses)
- have achieved a minimum cumulative GPA of 3.30
For further details on the AMP, refer to the AUS Undergraduate Catalog or the AMP webpage.
Blended Learning Mode of Delivery
The MSDAE program delivers several of its required and elective courses in a blended learning mode combining face-to-face teaching with online learning. Details about the delivery of the weekly sessions are provided in the course syllabi available from the department. Course assessments for courses delivered in blended learning mode are conducted in the same way as for courses delivered using the face-to face mode.
Degree Requirements
Students in the MSDAE degree program must choose from two options: the thesis option and the course option.
To qualify for graduation with a Master of Science in Data Analytics Engineering, students must successfully complete a minimum of 30 credit hours consisting of program core courses, program elective courses, a seminar and Master's Thesis (for students in the thesis option only), with a minimum cumulative grade point average of 3.00.
To ensure the MSDAE program provides students with a substantial research experience, both the thesis and the course options incorporate robust research components.
Students must complete the degree requirements within five years from the time of initial enrollment in the program.
Graduation residence requirements must be met. For details, refer to Graduation Requirements in the Academic Policies and Regulations section of the AUS Graduate Catalog.
Thesis Option
Students must successfully complete the following requirements:
- 9 credit hours in core courses
- a minimum of 12 credit hours in elective courses
- 9 credit hours in Master's Thesis
- a zero-credit hour seminar
Course Option
Students must successfully complete the following requirements:
- 9 credit hours in core course
- a minimum of 21 credit hours in elective courses
- a zero-credit hour seminar
Required Courses (18/9 credit hours)
Students in the thesis option must successfully complete a total of 18 credit hours in required courses consisting of 9 credit hours of core courses and a nine-credit-hour master's thesis.
Master's Thesis (9 credit hours-thesis only option)
DAE 699 Master's Thesis
Students in the course option must successfully complete 9 credit hours of core courses.
Core Courses (9 credit hours)
- DAE 500 Data Analytics Engineering and Visualization (blended learning mode)
- DAE 505 Optimization for Data Analytics Engineering (blended learning mode)
- DAE 515 Predictive Analytics and Machine Learning (blended learning mode)
In addition, all students must successfully complete a zero-credit seminar course (DAE 695).
Elective Courses (minimum of 12/21 credit hours)
Students in the thesis option must successfully complete a minimum of 12 credit hours in elective courses.
Students in the course option must successfully complete a minimum of 21 credit hours in elective courses.
Students may select their elective courses from the following list:
(minimum of 6/12 credit hours)
- DAE 610 Supply Chain Analytics (blended learning mode)
- DAE 615 Quality Engineering Analytics (blended learning mode)
- DAE 620 AI in Industrial Engineering Systems (blended learning mode)
- DAE 625 Big Data Analytics Engineering (blended learning mode)
- DAE 630 Engineering Consulting and Customer Analytics (blended learning mode)
- DAE 635 Emerging Technologies for Data Analytics (blended learning mode)
(maximum of 6/9 credit hours)
- ELE 648 Pattern Classification
- ELE 650 Deep Learning
- ESM 570 Project Management (blended learning mode)
- ESM 575 Advanced Engineering Economy (blended learning mode)
- ESM 625 Enterprise Resource Planning Systems (blended learning mode)
- ESM 638 Decision Analysis
With the approval of their advisor and the head of department, students may choose to take one graduate-level elective course outside the list of elective courses. The course must provide knowledge and skills that contribute to the program learning outcomes. The request must be approved by the student’s associate dean, who will inform the Office of the Registrar before course registration.
Students can elect to complete graduate level courses outside of the list of elective courses that do not meet the above conditions; such courses will not meet any of the degree program graduation requirements. Approvals of the student’s advisor and the student’s head of department are required.
Master's Thesis
A student in the thesis option must complete his/her Master's Thesis under the direct supervision and guidance of a principal advisor. This principal advisor serves as the chair of the student's examining committee. The committee also includes two additional faculty members. One of the additional faculty members must be selected from outside the program. The committee could also include one co-advisor or more.
A complete guide for preparing the master's thesis/professional project is given in the Graduate Studies Policies and Procedures document available on iLearn and accessible using the following path: iLearn-Community- Graduate Studies-Graduate Studies Policies and Procedures.
For registration details, please refer to Master's Thesis, Professional Project and Dissertation under the Academic Policies and Regulations section of the AUS Graduate Catalog.
