COVID-19 Updates:  See latest information for 2020/21 applicants, DkIT staff and students via our dedicated webpage  Read More.

new course

BSc (Hons) in Mathematics and Data Science

Course Duration
4 Years
Course Level
Level 8
Course Start Date
September

Two great reasons to consider this course

  • Data Analytics is identified, both nationally and internationally, as a key future skill and the demand for Data Scientists, Data Analysts and highly numerate graduates continues to grow alongside the massive amounts of available data.
  • This course will prepare students to work in the computing industry by helping to develop both their personal and professional skills in a supportive, positive, and student-centred environment .

Course Summary

This 4-year level 8 course is aimed at students who enjoyed Mathematics and Statistics at second level and are looking to develop the skills needed to enter the fast growing ICT sector, in particular in the area of Data Science and Data Analytics.

Data Analytics is identified, both nationally and internationally, as a key future skill and the demand for Data Scientists, Data Analysts and highly numerate graduates continues to grow alongside the massive amounts of available data. The course is well suited to numerate students who are looking to develop a more applied, industry focussed skillset than offered by traditional mathematics courses.

The course takes an integrative approach, focusing on first building strong foundational knowledge in the areas of Mathematics, Statistics and Programming, and later facilitating the synthesis of knowledge and practice from high-tech areas within the data and computing domains. The primary aim is to develop specialist knowledge in aspects of data required to become highly-skilled sought-after Data Analysts:

  • Fundamental and Advanced Statistics techniques
  • Applied Probability
  • Data Visualisation techniques that bring the data to life
  • Time Series Analysis to investigate copious amounts of time data and trends
  • Machine Learning, the fast paced and popular technique that is big data driven.

These skills will be built alongside essential programming capability and Systems knowledge: Programming in R & Python, Data/Big Data and Distributed Data Systems, while developing strong mathematical reasoning and in-depth understanding in areas of Computational Mathematics and Mathematical Analysis: Logic, Number Theory, Linear Algebra, Calculus and Mathematical Modelling.

YEAR 1

Semester 1

  • Data Science Fundamentals
  • Introduction to Programming for Data Analytics (year-long)
  • Probability & Statistics (year-long)
  • Pre-Calculus
  • Logic
  • Communication Skills

Semester 2

  • Bias in Computing
  • Tools for Software Development
  • Linear Algebra
  • Discrete Mathematics
  • Introduction to Programming for Data Analytics (year-long)
  • Probability & Statistics (year-long)

YEAR 2

Semester 1

  • Study Design
  • Database Systems
  • Object-Oriented Programming for Data Analytics (year-long)
  • Statistics (year-long)
  • Analysis 1 Geometry

Semester 2

  • Project Management
  • Big Data Systems
  • Number Theory
  • Analysis 2
  • Object-Oriented Programming for Data Analytics (year-
  • Statistics (year-long)

YEAR 3

Semester 1

  • Data Visualisation and Insight
  • Distributed Data Systems
  • Artificial Intelligence
  • Applied Probability Cryptography
  • Analysis 3

Semester 2

  • Work Placement
  • OR Approved Semester Abroad

YEAR 4

Semester 1

  • Research Methodology
  • Machine Learning (year-long)
  • Data Mining
  • Advanced Statistics 1
  • Project (year-long)
  • Differential Equations

Semester 2

  • Ethics & Professional Practice in Data Science
  • Time Series Analysis
  • Mathematical Modelling
  • Advanced Statistics 2
  • Machine Learning (year-long)
  • Project (year-long)

 

* All module titles are subject to change and are for indicative purposes only. The provision of electives each year is subject to numbers enrolling on each elective and available resources.

This course is delivered in a combination of lectures, lab classes and tutorials.

There are numerous support services available within the department to enable and encourage all students to realise their personal and professional potential.

This course builds advanced skills in programming, mathematics and statistics, databases and data mining, combined with highly developed problem-solving skills and will allow graduates to take on different roles in a variety of sectors. This course provides a stepping-stone to many others careers that value those who can think on their feet such as teaching, research and finance.

The typical roles that a graduate could take on include:

  • Data Analyst
  • Data Scientist
  • Data Wrangler
  • Data Curator
  • Data Architect
  • Business Analytics Specialist
  • Data Visualisation Developer
  • Junior Intelligence designer or Statistician

In additional to its industry focus, this programme also aims to provide a path for students wishing to pursue a 2nd level teaching career in Mathematics and Computer Science, dependent on Teaching Council requirements – graduates would be required to complete a Post-graduate Diploma in Education.

Graduates will have gained knowledge and developed advanced skills and competencies necessary to continue to an NFQ level 9 – Masters – or NFQ 10 doctoral programme – either taught, structured or by research.

Please find information on fees and funding here: www.dkit.ie/fees

Leaving Certificate Entry Requirements:

The standard Minimum entry requirements for this Level 8 ab-initio degree are:

Six grades at O6 or H7 in Leaving Certificate

INCLUDING At least two H5 Grades

AND Mathematics Grade O2 or H6

AND English Grade O6 or H7 OR Irish Grade O6 or H7

AND Minimum Points Score of 300.


Northern Ireland/UK Entry Requirements:

DkIT recognises Standard A Levels, Applied A Levels, BTECs and OCR Cambridge Technical

qualifications, or a combination of all four. To be eligible for a NFQ Level 8 programme,

applicants must meet the matriculation requirement of 6 different subjects which must

include:

• Mathematics at:

o GCSE: Grade B

o Or AS Level: Grade C

o Or A Level Grade E

• English (or Irish) at GCSE (Grade A* - C) or better

• Two subjects at either:

• ‘A Level’ (Grade A* - C)

• AND/OR Applied A-Level (Grade A* - C)

• AND/OR BTEC National Level 3 (National Award, Subsidiary Diploma, Extended

Certificate, 90-Credit Diploma, Foundation Diploma) (Grade Merit or

Distinction).

• AND/OR OCR Cambridge Technical Level 3 (Introductory Diploma, Extended

Certificate, Subsidiary Diploma, Foundation Diploma, 90-Credit Diploma) (Grade

Merit or Distinction)

• OR BTEC National Level 3 Diploma (Grade min: MM)

• OR OCR Cambridge Technical Level 3 Diploma (Grade min: MM)

• OR BTEC National Level 3 Extended Diploma (Grade min: MMP)

• The remaining subjects must be different from that presented above and may be

drawn from recognised subjects at:

• GCSE (Grade A* - C)

• AND/OR AS Level’ (Grades A - E)

Bachelor of Science (Honours) in Mathematics and Data Science

Department of Computing Science & Mathematics 8

• AND/OR A-level’ (Grades A* - E)

• AND/OR Applied ‘A-level’ (Grade A* - E)

• AND/OR BTEC National Level 3 (National Award, Subsidiary Diploma, Extended

Certificate, 90-Credit Diploma, Foundation Diploma, Diploma or Extended

Diploma*) (Pass, Merit or Distinction).

• AND/OR OCR Cambridge Technical Level 3 (Introductory Diploma, Extended

Certificate, Subsidiary Diploma, Foundation Diploma, 90-Credit Diploma,

Diploma or Extended Diploma*)(Pass, Merit or Distinction).

• And a minimum score of 300 points.

 

Students on the Bachelor of Science (Honours) in Mathematics and Data Science will undertake a 15 week work placement in year 3, semester 2 (semester 5). Students also have the option of undertaking a year of study abroad.

This course is for you if:

  • you are a logical thinker, with a passion for mathematics and wish to develop strong mathematical reasoning and problem-solving skills
  • you wish to develop the skills to allow you to extract meaningful ethical information from data, building analytical solutions that can provide invaluable insights and trends in varied contexts and industries
  • you wish to develop the skills and expertise to enter the fast growing data industry and to carve your own career-path in this and other sectors.

Dr Siobhan Connolly Kernan (Lecturer )
Email: Siobhan.ConnollyKernan@dkit.ie

Course ID DK823
Level 8
Duration 4 Years
School School of Informatics & Creative Arts
Department Computing Science and Mathematics
Awarding Body Dundalk Institute of Technology
Starting Date September
Apply to CAO

How to Apply

All applications for this course must be made directly to the CAO by using the course ID
DK823.

Apply On cao.ie

Northern Ireland & UK

Applicants from Northern Ireland/UK must also apply through CAO. Find out more information about
applying to DkIT from Northern Ireland or the UK.