Master of Science in Professional Studies: Data Analytics
About This Programme
This professional studies master's prepares participants to help organisations make better decisions through analytics, working with complex real-world data and creating value from it. Theory and practice are interlaced with continuous support from public and private sector partners, and RIT Dubai states that the programme was designed jointly with public bodies such as Smart Dubai and international organisations in the field. Designed for working individuals, it covers every level of analytics work: setting an organisation's strategy and vision for big data, securing data, building analytics infrastructure, and analysing and presenting data for decisions, including how data is used in artificial intelligence, virtual reality, robotics and machine learning. The 33-credit programme ends with a two-part thesis.
Course Highlights
- 33 credit hours, ending with a two-part thesis (PROF-776)
- Courses include Fundamentals of Data Analytics, Enterprise Infrastructure for Data Analytics, Foundations of Data Mining, Visual Analytics and Information Security Risk Management
- Students can apply what they learn at their workplace while they study
- IELTS 6.0 or EmSAT 1400 accepted, as for RIT Dubai's other professional studies programmes
- Accredited by the UAE Ministry of Higher Education and Scientific Research
What You'll Study
RIT Dubai publishes a typical course sequence of 33 credit hours, including a proposal seminar and a two-part thesis.
Typical course sequence
- PROF-705 Context and Trends3 credits
- PROF-740 Fundamentals of Data Analytics3 credits
- PROF-741 Enterprise Infrastructure for Data Analytics3 credits
- PROF-770 Proposal Seminar0 credits
- PROF-790 Data Analytics for Emerging Technologies3 credits
- PROF-792 Data Analytics Transformations3 credits
- ISTE-600 Foundations of Data Mining3 credits
- ISTE-780 Data Driven Knowledge Discovery3 credits
- ISTE-782 Visual Analytics3 credits
- CSEC-733 Information Security Risk Management3 credits
- PROF-776 Thesis Part 13 credits
- PROF-776 Thesis Part 23 credits
What You'll Learn
Programme learning outcomes
- Evaluate business problems for analytical investigation and decision-making
- Build comprehensive analytical models
- Compare data collection and preparation techniques used in building models
- Apply data analysis models and methods to large-scale data and emerging technologies
- Identify and analyse the risks of data analytics
- Show competence in innovation, entrepreneurship and sustainability
- Carry out a research-based data analytics project with findings and recommendations
Programme goals
- A thorough understanding of the tools used to sort, mine, visualise and analyse data
- The ability to apply those tools to a wide variety of data and produce high-quality research
Entry Requirements
Applicants submit a CV showing professional work experience in the area of study, two letters of recommendation and a personal statement of about 500 words. Final admission decisions are made by RIT's Graduate Department in Rochester, New York.
Careers
Typical job titles: Data Scientist, Data Engineer, Data Architect, Machine Learning Engineer, Data Analyst, Database Administrator, Statistician, Business Analyst.
Accreditation & Professional Recognition
Accredited by the UAE Ministry of Higher Education and Scientific Research, and listed as Active on the Commission for Academic Accreditation's register. The degree is issued by RIT's main campus in Rochester, New York.
Programme Details
Award
Master of Science (MS)
Start Date
August (Fall) and January (Spring)
Typical Offer
Bachelor's degree with about a 3.0 GPA
Qualification
MS
Subject Area
Data Science & AI
Campus
Dubai Silicon Oasis
Tuition Fee
AED 128,700 total
RIT Dubai accepts applications for Spring (January) and Fall (August) intakes. Spring: early admission until 31 October, regular admission until 31 December, deadline 8 January. Fall: early admission until 15 January, regular admission until 31 May, deadline 22 August. RIT Dubai offers scholarships of up to 50% based on academic and non-academic achievements.