Classroom - Daytime
Information and communication (including ICT)
Frances McAuliffeEmail Phone
Department of Mathematics,
Cork Institute of Technology,
CIT's HDip in Data Science and Analytics has been designed and developed in collaboration with industrial experts in the field of Data Science. The programme aims to furnish students with the necessary skillsets to enter the world of data science and analytics through building strong foundations in the core competencies of Statistics, Computer Science and Data Science. This higher diploma introduces students to topics including statistical modelling, regression, classifiers, decision trees, databases, time series forecasting and machine learning while also providing the learner with the required technical skills in software packages and programming languages such as R, Python, Excel, SQL, NoSQL, Tableau, Spark and Hadoop.
On successful completion of this programme, the learner will be able to:
1. Demonstrate detailed knowledge and understanding of areas of Mathematics, Statistics, Computer Science and Business Intelligence relevant to the Data Analyst.
2. Demonstrate understanding of the terminology, defining concepts and theories underlying the Data Science and Analytics field; demonstrate knowledge of the advanced methods and technologies for acquiring, interpreting and analysing big data, with a critical understanding of the appropriate contexts for their use; relate current issues in Data Science to society; understand current knowledge of the Data Science field, including current limits of theoretical and applied knowledge.
3. Demonstrate mastery of relevant skills and tools in Statistics, Mathematics, Computer Science and Business Intelligence; use these to solve complex problems involving big data sets; interpret and apply appropriate and referenced literature and other information sources; work independently within defined time and resource boundaries; communicate scientific information in a variety of forms to specialist and non-specialist audiences.
4. Formulate and test hypotheses; design experiments; appreciate current limits of knowledge in the Data Science field and respond appropriately; think independently and make effective decisions; contribute fully to the day-to-day operations of the Data Science work setting.
5. Apply data analysis skills and technologies in a range of contexts in order to critically interpret existing knowledge and apply in new situations; make and report appropriate decisions in a responsible and ethical manner.
6. Act effectively under guidance in a peer relationship with qualified practitioners; participate constructively in a complex interdisciplinary team environment; plan for effective project implementation; reflect on own practices.
7. Learn to act in variable and unfamiliar learning contexts; identify learning needs and undertake continuous learning in the Data Science field; assimilate and apply new learning.
8. Demonstrate an understanding of the wider social, political, business and economic contexts of Data Science, including an appreciation of the philosophical and ethical issues involved.
Applicants will already hold a Level 8 degree, and must be highly motivated and capable of independent learning. Preference will be given to jobseekers 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 http://www.cit.ie/rpl for further details).
CIT's Higher Diploma in Science in Data Science & Analytics (NFQ Level 8) 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. This is a full-time 60 credit programme, in which three core strands – Statistics, Mathematics, Computer Science and Data Science – are developed and interleaved over two semesters.
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 and Analytics. Contact hours for the course will take place in the morning and afternoon. Graduates of the programme will have gained significant practical experience, in software packages and programming languages including R, Python, Excel, SQL, NoSQL, Tableau, Spark and Hadoop for example.
The programme aims to produce graduates that are of a high academic and practical standard, in order to match the growing needs of the Irish and international IT industry, especially in the 'Big Data' space. The graduate will be able to ally the transferable skills obtained in their 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 those 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. By equipping graduates with the scientific, technological, business and interpersonal skills necessary to operate professionally in this rapidly evolving interdisciplinary field, the programme seeks to position graduates at the interface of the world’s data revolution.
Here is some feedback from recent graduates of the Higher Diploma in Science in Data Science & Analytics:
1. A recent HDip student who is also a Civil Engineering graduate, and who previously worked as a senior design engineer:
"This has been a fantastic course. The workload was significant but the quality and attentiveness of the staff was second to none throughout. In addition the exposure to a wide range of technologies will really stand to the class when it comes to seeking work. This course has been the most enjoyable learning experience I’ve ever had."
2. A recent HDip graduate who holds both BSc (Hons) and MSc degrees in the Life Sciences field:
"The Higher Diploma in Data Science and Analytics is a great computer conversion course and involves a lot of practical computer work when it comes to using technologies in this field. Having started with no hands on computational experience, but with a massive interest in science and computing, I feel that I have learnt all the skills necessary to obtain a job in IT, but also to enhance the research skills I had developed in my undergraduate studies. There are loads of avenues available to explore after completing the course. It’s an excellent course for delving into the world of analytics and I would recommend the course to anyone interested in the area. It helps also that the course is provided with excellent mentors at CIT, who always seem to keep things interesting and accessible."
3. A BA (Mathematics & Computer Science) and HDipEd graduate who subsequently took and graduated with the HDipSc in Data Science & Analytics:
"The H Dip in Data Science & Analytics was an interesting, varied, challenging and relevant course. We had access to a Virtual Machine environment. This was superb and meant we had 24/7 access to CIT I.T. resources, with all the software available that was needed for the varied coursework. The lecturers were all top quality and were always engaging and welcomed input from the class."
4. A recent HDip graduate who previously graduated with a BA in Mathematics and Economics and who has also worked in the financial sector:
"The Higher Diploma in Data Science & Analytics is a great course for anyone interested in IT and Big Data. The course is intensive and challenging, but very rewarding. The topics covered were very interesting, such as machine learning, data mining and statistics. The course was well run, the lecturers were very supportive and there are great resources provide by the college. All in all, a challenging, yet hugely enjoyable course."
5. A recent HDip graduate who is also a Commerce graduate and who has previously worked as a commercial analyst and account manager:
"The Data Science & Analytics Diploma proved to be both challenging and motivating, with endless support throughout the year. Many subjects were introduced that offer a great foundation for a career in analytics, while at the same time refreshing dormant skills. It was a tough, but rewarding year."
6. A recent HDip graduate, with a prior degree in Accounting:
"I thought it was an excellent course that I learned a lot from. I enjoyed doing it and it was of great benefit to me. It was also highly interesting for me. I would highly recommend it."
Sample careers include those in:
ICT industry, Public Sector (e.g. CSO, CAO, government departments), Finance, Health, Insurance, Telecoms, large retail companies, SMEs.
Specific Skills Area(s) include:
Data Science & Analytics (statistical & analytical skills, business skills, communication skills), Internet Security, Computer Programming, Hadoop Skills.
Sample Job Titles include:
Data Analyst, Data Scientist, Statistician, Computer Programmer, Database Programme Operator, Business Analyst, Hadoop Developer.
Here is some information about the Cork Big Data and Analytics Group, with which CIT is pleased to be associated:
The Cork Big Data and Analytics Group is a community based initiative formed of professionals and students who are interested in using machine learning/data mining/analytical approaches to solve problems on large publicly available datasets. Members range from those working in this space professionally to those interested in simply finding out more. CIT proudly supports this initiative by housing them on campus for their monthly meetups. Indeed a student from the 2014/2015 cohort (who was a prizewinner in the AIB Datathon) is a prominent member in this group, and led a recent educational seminar for members of the application of deep learning methods.
This is a full-time programme run over two semesters. In Semester 1 (September to December, with examinations in December and early January), there are 24-26 contact hours per week, and the learner will normally need to allocate an additional 18-20 hours per week to independent learning. In Semester 2 (February to the end of May), there are 16-17 contact hours per week, and the learner will normally need to allocate an additional 26-28 hours per week to independent learning (including work on the capstone project).
Cork Institute of Technology Bishopstown Campus
The Admissions Office, CIT, Bishopstown, CorkEmail
Apply online through www.springboardcourses.ie
Please upload a current Curriculum Vitae, a Personal Statement and scanned copies of the documents listed below:
1. Personal Statement - Please include a 300 word personal statement detailing what has motivated you to undertake the programme and how the programme fits in with your career objectives.
2. Educational Transcripts for any qualifications listed in your application form.
3. Final Certificates for any qualifications listed in your application form.
4. Please also include 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. (You must provide evidence by way of final certificates).