share this page

Higher Diploma in Science in Data Science & Analytics - Part-time

  • Course Code


  • Field of Study

    Data Science & Analytics

  • Type of Course:

    Higher Diploma

  • Type of Qualification:


  • Type of Study:

    Part time

  • Application Closing Date:

Admission Requirements:

Applicants will already hold a Level 8 degree, and must be highly motivated and capable of independent learning. Preference will be given to applicants with a background in cognate and analytical disciplines, who would benefit from an opportunity to rapidly and successfully convert their qualifications to industry relevant ICT skills. All candidates with a Level 8 qualification or equivalent will be considered.

Candidates with a Level 7 qualification and significant relevant experiential learning may be eligible through our recognition of prior learning processes. Please see for further details.

Course summary

This course has been designed to address the skills shortage in Data Science & Analytics, by equipping graduates with the scientific, technological, business and interpersonal skills necessary to operate professionally in this rapidly evolving interdisciplinary field.



All part-time programmes at CIT will run subject to sufficient student numbers. Where a programme cannot proceed, applicants will be contacted and advised on alternative study options.

Students should note that Fees quoted relate to the academic year 2017-2018 only and are subject to change on an annual basis. Except where stated, course fees cover the cost of tuition only. 

Course fees must be paid before attending lectures.

An Information/Registration session will take place on Wednesday 6th September from 6.00pm to 8.00pm at the CIT Bishopstown Campus. Institute staff will be in attendance to offer career guidance and assistance.


Fees: €350 per 5 credit module, and €700 for the 10 credit project module. These fees include examination fees. Thus the total fee for the full 60 credit programme is €4200.  
Students pay for the relevant modules at the start of each semester. 

2 Years Part-time.
January/February 2018 – depending on the start date of Semester 2 (subject to demand)


This course has been designed to address the skills shortage in Data Science and Analytics, by equipping graduates with the scientific, technological, business and interpersonal skills necessary to operate professionally in this rapidly evolving interdisciplinary field.

The graduate of this programme will be of high academic and practical standards, in order to match the needs of the Irish and international IT industry, especially in the “Big Data” space. He/she will be able to ally the transferable skills obtained in his/her Level 8 degree to newly acquired knowledge, skills and competences in Statistics & Mathematics, Computer Science and Data Science, and their application to solving real-life problems. Potential job opportunities not only include that of data scientist/analyst, but also skilled staff who will be required to extract actionable insight from large amounts of raw data in order to enable better decision making within an organisation.


This is a 60 credit programme, in which three core strands: Statistics & Mathematics, Computer Science, and Data Science, are developed over two semesters, with an increasing specialisation to the “big data” context. There will be significant opportunity throughout to apply theoretical knowledge and develop problem solving skills through practical and laboratory sessions. The learner will also undertake a capstone project, which will be a key opportunity to demonstrate the ability to synthesise the learning acquired in the programme, and to apply it to the solution of an authentic problem in Data Science & Analytics.

The graduate will gain significant practical experience, in software packages such as R, Excel, VBA, SAS, SPSS, RapidMiner, Tableau, Hadoop and Qlikview, and in the programming languages Python, SQL and NoSQL.

Click on the Modules tab above for further information and module descriptors.


Higher Diploma in Science in Data Science & Analytics  (Level 8 on the National Framework of Qualifications).



Detailed module descriptors are available here.

Calendar & Contact hours


Subject to demand and the availability of eligible applicants, it is planned to start delivery of this two year part-time programme on Monday 30th January 2017. The following is an overview of the academic calendar for the programme. Please note that, at the time of writing, the CIT academic calendars for 2017/18 and 2018/19 remain to be confirmed.


First Semester: 30th January 2017 to June 2017

  • Lectures/tutorials/labs run from Monday 30th January to Friday7th April and from Monday 24th April to Friday 12th May
  • Easter holidays – weeks of Monday 10th April and Monday 17th April
  • Examination period: Monday 15th May to Friday 26th May inclusive
  • Module results available mid- to late June


Provisional Programme Timetable for First Semester

CIT Bishopstown,
room t.b.c.
Applied Statistics & Probability
CIT Bishopstown, 
room t.b.c.
Data Science & Analytics
CIT Bishopstown, 
room t.b.c.
Analytic & Scientific Programming


Second Semester: September 2017 to January 2018

  • Lectures run from September to mid-December
  • Examinations in mid-December and early January
  • Module results available in early February


Third Semester: end January 2018 to end May 2018

  • Lectures run from the end of February to mid-May
  • Examinations from mid-May to end of May
  • Module results available mid- to late June

Fourth Semester: September 2018 to January 2019

  • Lectures run from September to mid-December
  • Examinations in mid-December and early January
  • Module results and overall programme result available in early February
  • Conferring in Spring/Summer 2019


Contact hours

For the first three semesters, the programme will be delivered on campus in CIT Bishopstown, on three evenings per week, with one 5 credit module running per evening. The number of contact hours per evening is 3-4 hours (6pm-10pm or 7pm-10pm, depending on the module). There are no contact hours on Fridays/Saturdays/Sundays.

NB: for each 5 credit module, the average learner workload also involves 3-4 hours for independent learning (review of module material, preparation for assessments, completion of assignments, etc.) 

In the fourth and final semester, the learner shall complete a 10 credit capstone project and shall take one taught 5 credit module. Thus the number of contact hours will decrease to 3.5 hours – 4.5 hours, to include a weekly one-to-one 30 minute meeting with the project supervisor. 

In summary, over the four semesters, the student should expect to commit an average of 21 hours per week to the programme, to include contact hours (lectures/labs/tutorials) and independent study.


Click on the above link to the module descriptors for further information about contact hours.

  • Online application will open shortly for Semester 2 commencing in January/February 2018.
  • Please note that applicants will be required to pay an acceptance fee of €550 online if a place on a course is offered. This fee is deductible from the overall course fee.

  • Please attach and upload any documents such as transcripts, CV, other details relevant to the application.

Apply Now >>



Please upload the following documents when making your application:

  1. A current Curriculum Vitae
  2.  Personal Statement - please include a 300 word personal statement detailing what has motivated you to apply the programme and how the programme fits in with your career objectives.
  3. Any further information which you think would support your application, for example, information in regard to Higher Level grades in Leaving Certificate Mathematics, Leaving Certificate Applied Mathematics, Leaving Certificate Physics.
  4. Educational transcripts and/or final certificates for any qualifications listed in your application form.



Frances McAuliffe
021 432 6187