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Data Science with Year of Professional Experience

1 Study option · UndergraduateMain Site
Awarded by:
Queen’s University Belfast

Course summary

The aim of the programme is to offer a deep and up-to-date education in data science, machine learning and artificial intelligence that prepares graduates with key knowledge, skills and competencies necessary for employment in data engineering, data analysis, data architect (as well as managerial positions on those topics), or as preparation for further research and innovation careers.

In particular the programme aims to provide students with:

  • Comprehensive knowledge and understanding of the fundamental principles of artificial intelligence, data science and machine learning, which will remain applicable through changes in technology.

  • Advanced knowledge and practical skills in the theory and practice of data analytics.

  • The necessary skills, tools and techniques needed to embark on careers as data scientist, or professional developers skilled in data science.

  • Skills in a range of practices, processes, tools and methods applicable to data science in commercial and research contexts.

  • Timely exposure to, and practical experience in, a range of current technologies and emerging trends at the forefront of data science, such as Deep Learning, Natural Language Processing and Trustworthy AI.

  • Opportunities for the development of practical skills in a commercial context.

Data Science With Year Of Professional Experience Degree HighlightsIndustry Links

Our students are constantly given the opportunity to put theory into practice. We regularly consult a large number of employers including, for example, Civica and Sensata Technologies, who provide sponsorship for our students as well as Kainos and Liberty IT who are members of the employer liaison panel for the course.

In addition, students will complete a year of professional experience on data analytics with one of our partners companies.

World Class Facilities

A new Teaching Centre for Mathematics and Physics opened in September 2016. This provides a dedicated space for teaching within the School. Facilities for mathematics include new lecture and group-study rooms, a new student social area and state-of-the-art computer facilities. Computer Science teaching takes place in the Computer Science Building on the Malone Road, just a short walk from the Mathematics department. The building was recently refurbished at a cost of £14M, and is welcoming with a modern style and approach to students with spaces which include computer laboratories, lecture theatre and options of break-out areas.

How to apply

Application codes

Course code:
G420
Institution code:
Q75

Historical entry grades data BETA

This section shows the range of grades students (with UK A-Levels or Pearson BTEC Level 3 National Extended Diplomas) who received offers were previously accepted with (learn more). It is designed to support your research but does not guarantee whether you will or won't get a place. Admissions teams consider various factors, including interviews, subject requirements, and entrance tests. Check all course entry requirements for eligibility.

Data from:
This course and 13 other mathematics courses
Date range:
2022-2024

Offer rate for UK school & college leavers

99% Students aged 17/18 who applied to this course were offered a place.

How do you compare?

See how students with your grades have been accepted onto this course in the past.

Student Outcomes

Operated by the Office for Students

70 Employment after 15 months (Most common jobs)

90 Go onto work and study

The number of student respondents and response rates can be important in interpreting the data – it is important to note your experience may be different from theirs. This data will be based on the subject area rather than the specific course. Read more about this data on the Discover Uni website.

Fees and funding

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