Master of Science in Data Analytics Engineering
About This Programme
A 30-credit blended-delivery master's in data analytics engineering, optimisation, predictive analytics and machine learning applied to supply chain, healthcare, manufacturing and government. Prepares graduates to lead data initiatives and digital transformation.
Course Highlights
- Engineering-focused analytics degree from the Department of Industrial Engineering
- Core in data analytics and visualization, optimization, and predictive analytics and machine learning
- Electives on supply-chain analytics, quality engineering analytics, big data and AI in industrial systems
- Applied across supply chain, healthcare, manufacturing and government
What You'll Study
Thesis option (9 core + 12 elective credits + 9-credit thesis) or course option (9 core + 21 elective credits + seminar). Offered by the Department of Industrial Engineering.
Core Courses (9 credits + 0-credit seminar)
- DAE 500 Data Analytics Engineering and Visualization3 credits
- DAE 505 Optimization for Data Analytics Engineering3 credits
- DAE 515 Predictive Analytics and Machine Learning3 credits
- DAE 695 Seminar0 credits
Program Elective Courses (min 6/12 credits)
- DAE 610 Supply Chain Analytics3 credits
- DAE 615 Quality Engineering Analytics3 credits
- DAE 620 AI in Industrial Engineering Systems3 credits
- DAE 625 Big Data Analytics Engineering3 credits
- DAE 630 Engineering Consulting and Customer Analytics3 credits
- DAE 635 Emerging Technologies for Data Analytics3 credits
Cross-listed Elective Courses (max 6/9 credits)
- ELE 648 Pattern Classification3 credits
- ELE 650 Deep Learning3 credits
- ESM 570 Project Management3 credits
- ESM 575 Advanced Engineering Economy3 credits
- ESM 625 Enterprise Resource Planning Systems3 credits
- ESM 638 Decision Analysis3 credits
Thesis (thesis option only)
- Master's Thesis9 credits
Entry Requirements
MBA and MBDA applicants take the GMAT or the AUS admission test; a statement of purpose is required for some programmes.
Careers
Data and analytics engineering roles leading data initiatives and digital-transformation efforts across supply chain, healthcare, manufacturing and government.
Accreditation & Professional Recognition
Licensed/accredited by the UAE Commission for Academic Accreditation (CAA), Ministry of Higher Education and Scientific Research; AUS is institutionally US-accredited by MSCHE (Middle States).
Programme Details
Award
Master of Science in Data Analytics Engineering
Start Date
August 2026 (Fall; Spring intake for many programmes)
Typical Offer
BS in Engineering, CGPA 3.0/4.0, plus IELTS 6.5 (or TOEFL iBT 80). Related quantitative-science degrees considered case-by-case.
Duration
2 years
Qualification
Masters
Subject Area
Engineering
Campus
Sharjah
Course Type
Master of Science
Study Pattern
Full time
Delivery Format
Blended
Tuition Fee
AED 82,200/yr
Apply online at apply.aus.edu with transcripts, a CV, references and a statement of purpose where required. The graduate application fee is AED 450 + 5% VAT. AUS offers graduate assistantships to qualified applicants.