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Higher Diploma in Science in Data Analytics (Part-Time)

Course Points
60
Course Duration
2 Years
Course Level
Level 8
Course Start Date
Tuesday 17th September 2024

Four great reasons to consider this course

  • This course is ideal for numerate graduates looking to enhance their skills and improve their employability in the field of Data Analytics.
  • It is delivered by highly qualified lecturers with significant professional experience.
  • Underpinned by concrete theories, this course provides real practical statistics and computing skills that can be used to solve business problems across a wide range of industries.
  • This course is delivered through a blended combination of online and onsite learning.

Course Summary

This two year part-time course will equip participants with the theoretical and practical skills to enter the world of data analytics. It will provide learners with the required skills in the areas of statistics, programming and databases that will enable them to transfer much of the domain specific knowledge/skill already gain in their primary degree(s) to the IT and Data Analytics sector.

Important notice about this course

NOW ENROLLING

This course is supported by Springboard+. You can find more information on Springboard by clicking here.

If you are unemployed and in receipt of a jobseekers payment (including Farm Assist and Qualified Adults of Working Age) you are NOT eligible for two-year ICT Conversion courses.

This course is aimed at candidates with strong numeracy skills and a basic knowledge of statistics who wish to become more data savvy, no prior programming exposure is required. This course is created for those who wish to develop the skills, expertise and knowledge to work as Data Analysts and is aligned with the needs of local data focused companies. 

Course Schedule:

Stage 1 / Semester 1

  • Statistics using R - 1 
  • Spreadsheet Data Analytics
  • Research Methods for Data Analytics

Stage 1 / Semester 2

  • Ethics and Social Responsibility in Data Analytics
  • Applied Database Systems
  • Statistics using R - 2 


Stage 2 / Semester 1

  • Advanced Statistics using R - 1
  • Real Time Data Analytics
  • Data Analytics Project 1


Stage 2 / Semester 2

  • Data Visualisation
  • Advanced Statistics using R - 2
  • Data Analytics Project 2 

This course is delivered using a blended learning approach with weekly interactive and hands-on practical lab-based sessions supported by independent and online learning.

This course will run over 2 years, with online synchronous classes delivered on two evenings per week, typically Monday and Wednesday 6pm to 9pm, with an additional 1-2 asynchronous contact hours (videos/practical tasks) to be completed within the same week, but at a time of the students choosing.

Weekly classes will be interactive, with hands-on practical lab-based sessions supported by independent and online learning. Participants are required to attend online synchronous classes as this will be necessary in order for them to master the materials.

Any End-of-semester final exams will take place onsite in DkIT, and participants will be required to attend. 

The course provides the necessary preparation for a career in areas such as

  • Data Analyst;
  • Data Scientist;
  • Data Engineer;
  • Business Analytics Specialist;
  • Data Visualization Developer;
  • Analytics Manager

On the successful completion of this Higher Diploma, students who obtain Second Class Honours, or higher, will be eligible to be considered for entry to an MSc in Computing programme (taught or research). Future progression options available within DkIT will include the MSc in Data Analytics.  

On the successful completion of this Higher Diploma, students who obtain Second Class Honours, or higher, will be eligible to be considered for entry to the PGDip in Science in Data Analytics or the MSc in Data Analytics programme (taught, structured or research) offered by DkIT.

€570 (Springboard Supported) payable by 31st October

ANY Honours (Level 8) Degree with 15 credits of Mathematics

and/or

Statistics OR Level 7 Degree with 15 credits of Mathematics and/or Statistics AND at least 2 years of work experience together with strong numeracy skills.

No prior programming exposure is required.


To apply for this programme via the Springboard+ scheme, you must meet the eligibility criteria (click to read) in addition to the minimum entry criteria listed above.  

If you are unemployed and in receipt of a jobseekers payment (including Farm Assist and Qualified Adults of Working Age) you are NOT eligible for two-year ICT Conversion courses.

Graduates with strong numerate skills who wish to pursue a career in the expanding area of Data Analytics.

Professionals who wish to develop their Data Analytics and Mining skills to apply them to real problems in their current work domains.

Graduates who enjoy Mathematics and problem-solving with a focus on real-world problems.

Graduates who are interested in developing their advanced statistical and computing skillsets to master areas such as statistical inference and machine learning.

Dr Kevin McDaid (Dr Abhishek Kaushik)
Email: abhishek.kaushik@dkit.ie

Dr Fiona Lawless (Head of Computing Science and Mathematics)
Phone: +353 42 9370200
Email: fiona.lawless@dkit.ie

Course ID DK_ICHDA_8
Course Type Flexible & Professional, Springboard
Study Mode Part-Time
Level 8
Duration 2 Years
Fees €570 (Springboard Supported)
Starting Date Tuesday 17th September 2024
School School of Informatics & Creative Arts
Department Computing Science and Mathematics
Credits 60
Awarding Body Dundalk Institute of Technology
Delivery Method Online

How To Apply

Apply on Springboard Portal

Applications for this course are now being accepted through the Springboard portal.

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).