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Undergraduate

BSc (Hons) in Mathematics and Data Science

From Data to Insights, make problem solving your profession
DK823
310 Points

CAO Code

DK823

Start Date

September 2024

Duration

4 Years

Work Placement

Yes

NFQ Level

8

Discipline Area

Computing

Course Type

Undergraduate

Study Mode

Full-Time

Delivery

On Campus

Course Overview

The course builds strong foundational knowledge in the areas of Mathematics, Statistics and Programming. Well-rounded computing skills are developed allowing students to focus in on high-tech areas within the data and computing domains.

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.

What makes this course different

Work Placement or Study Abroad

There is a 15-week work placement in Year 3 and study also have the option of undertaking a year of study abroad.

Pathway to Teaching

Students who complete the course can progress to complete a Post-graduate Diploma in Education, which depending on Teaching Council requirements, would allow them to move into a career in secondary school teaching in Mathematics and Computer Science.

Great Career Prospects

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.

Understanding the Industry

Data Science is the study of information - where it comes from, what it tells us and how to turn it into a valuable resource which enables businesses to make decisions, solve complex problems and create strategies to improve results and performance. Data is being used increasingly in every industry, not just computing. From finance and healthcare to sporting and commercial businesses. People capable of pulling solutions from data’s patterns are becoming increasingly valued employees.

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 continue 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.

Career Opportunities

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.

Future Careers:

  • Data Scientist
  • Sport Analyst
  • Healthcare Statistician
  • Data Analyst
  • Data Visualization Developer
  • Junior Intelligence Designer
  • Statistician

In these areas:

  • Banking
  • Finance
  • Healthcare
  • Sport

Course Delivery and Modules

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.

  • Year 1

    • Introduction to Programming for Data Analytics
    • Probability & Statistics
    • Data Science Fundamentals
    • Pre-Calculus
    • Logic
    • Communication Skills
    • Bias in Computing
    • Tools for Software Development
    • Linear Algebra
    • Discrete Mathematics
  • Year 2

    • Object-Oriented Programming for Data Analytics
    • Statistics
    • Study Design
    • Database Systems
    • Geometry
    • Analysis
    • Project Management
    • Big Data Systems
    • Number Theory
  • Year 3

    • Data Visualisation and Insight
    • Distributed Data Systems
    • Artificial Intelligence
    • Applied Probability
    • Cryptography
    • Analysis
    • Work Placement (15 weeks) OR Approved Semester Abroad
  • Year 4

    • Project
    • Machine Learning
    • Research Methodology
    • Data Mining
    • Differential Equations
    • Advanced Statistics
    • Ethics & Professional Practice in Data Science
    • Time Series Analysis
    • Mathematical Modelling

Work Placement

Students undertake a 15-week work placement in year 3. Students also have the option of undertaking a year of study abroad.

Education Progression

Postgraduate 1 - 2 Years On Campus

MSc in Data Analytics

View Course Details

Fees and Funding

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

Entry Requirements

In addition to the standard entry requirements below, Maths Grade 02 or H6 is also required. Applicants from NI/UK require a GCSE Maths Grade A or AS Level Grade C or A Level Grade E.

Recent CAO Points

2023 CAO Round 1 Points

310

How To Apply

Apply on CAO

All standard entry first-year applicants must apply for entry through the CAO. See Important application dates for CAO and information for specific applicant types below:

CAO Code: DK823
Apply on CAO

Advanced Entry & Transfer Applications

Advanced Entry is for applicants who have previous educational achievements and/or work experience and want to be considered for direct entry into year  2, 3, or 4 of a course. This includes students looking to transfer to DkIT from another Higher Education provider.

Closing Date: 6th June
Apply Now

International Application (non-EU)

International Applicants (not from or living in the EU) can apply through an agent or directly to DkIT to study this course.

Ask us a Question

If you have a question about the BSc (Hons) in Mathematics and Data Science please ask it below and we will get back to you.


Dr Siobhan Connolly Kernan

Lecturer

Email: Siobhan.ConnollyKernan@dkit.ie

Disclaimer: All module titles are subject to change and for indicative purposes only. All courses are delivered subject to demand and timetables are subject to change. Elective Module options will only run subject to student numbers. The relevant Department will determine the viability of each elective module option proceeding depending on the number of students who choose that option. Students will be offered alternative elective modules on their programme should their preferred elective option not be proceeding. Award Options for Common Entry Programmes: The relevant Department will determine the viability of each award option proceeding depending on the number of students who choose either option. If the numbers for one of the Award options exceed available places, students for this option will be selected based on Academic Merit (highest grades).