Course Overview
Professionals with the ability to interrogate datasets by applying analytical techniques to describe and predict business performance are in high demand worldwide.
The first semester modules focus on core topic areas such as business intelligence and analytics, data warehouse design, and big data applications, enabling you to gain insights into large multivariate datasets and apply your problem-solving abilities to explore business opportunities and challenges data scientists face when using business intelligence systems.
In the second semester, you will apply your technical knowledge and further progress your analytical expertise by focusing on specific data science subject areas such as data mining techniques and methods. You will also be encouraged to demonstrate your technical and analytical abilities in response to real-world problems during your final-semester individual project.
Our graduates will leave with sought-after skills for business intelligence and data mining roles within any field of data science. Opportunities also exist for further academic study towards a doctorate and a research career.
Key features
- Designed to equip you with the technical expertise needed for a career in industry, this course will hone you for roles suited in the field of analytics and business intelligence.
- Students will gain insight into real-world issues and solutions through research groups. You will have the opportunity to attend guest lectures and seminars. The curriculum features Apache Spark and the Hadoop Distributed File System to demonstrate data mining and machine learning algorithms.
- Our dedicated computing laboratories fully equipped with HP dual-boot, all-in-one computers and a high-performance file server.
- The university's commitment to staying at the forefront of technological advancements is evident in its partnerships with industry, which provide students with valuable networking opportunities and enterprise connections.
- Students on the Dubai campus will benefit from the same high-quality education and industry-relevant curriculum. Additionally, students will have access to state-of-the-art facilities and resources, ensuring they are well-equipped to excel in their studies and future careers in data science.
- DMU Dubai students can now benefit from the Industry Advisory Board, which comprises leading experts and professionals at the enterprise level. The board provides valuable insights and guidance to ensure the curriculum remains relevant and current with industry trends and demands.
- Benefit from Education 2030, where a simplified ‘block learning’ timetable means you will study one subject at a time and have more time to engage with your learning, receive faster feedback and enjoy a better study-life balance
- Applicants will typically hold an undergraduate degree with a minimum pass of 2:2 or equivalent overseas qualification.
- Professional qualifications deemed to be of equivalent standing will be considered on an individual basis.
- Work experience is not a requirement. However, applications from those without formal qualifications but with significant professional experience in the relevant field will be considered individually.
If English is not your first language an IELTS score of 6.0 or equivalent when you start the course is essential.
Education 2030
We want to ensure you have the best learning experience possible and a supportive and nurturing learning community. That’s why we’re introducing a new block model for delivering the majority of our courses, known as Education 2030. This means a more simplified timetable where you will study one subject at a time instead of several at once. You will have more time to engage with your learning and get to know the teaching team and course mates. You will receive faster feedback through more regular assessment, and have a better study-life balance to enjoy other important aspects of university life.
Read more about Education 2030Course modules
- Data Analytics Infrastructure
- Big Data Applications
- Data Mining Techniques and Methods
- Project proposal, Planning and project management (PPPM)
- PGT Project
Note: All modules are indicative and based on the current academic session. Course information is correct at the time of publication and is subject to review. Exact modules may, therefore, vary for your intake in order to keep content current. If there are changes to your course we will, where reasonable, take steps to inform you as appropriate.
Teaching and assessments
Teaching will normally be delivered through formal lectures, informal seminars, tutorials, workshops, discussions and e-learning packages. Assessment will usually be carried out through a combination of individual and group work, presentations, reports, projects and exams.
First semester modules introduces business intelligence, analytics and data infrastructure as well as big data applications so that you can gain insights and practice of using business intelligence systems and analytics programming to exploit multidimensional data sets.
In the second semester you are exposed to a variety of data mining techniques and methods available and interpreting the statistical results in relevant problem domains. A further module prepares students to undertake an individual research project. This project module allows you to undertake extensive research into an aspect of big data, and/or provides an opportunity to develop and demonstrate your analytical and processing abilities in response to a given practical problem.
Contact and learning hours
Students will normally attend around 12 hours of timetabled taught sessions each week, and can expect to undertake around 24 further hours of self-directed independent study and research to support your assignments and dissertation per week.
Meet your programme leader
