Postgraduate Diploma in Science in Data Analytics

Course Instance ID:	1049411986
Description:	Postgraduate Diploma in Science in Data Analytics
Duration:	1 year
NFQ Level:	Level 9

This course aims to produce technically competent, innovative graduates that will become leading practitioners in the field of data analytics. Upon completion, graduates will be able to:

Conduct independent research and analysis in the field of data analytics
Demonstrate expert knowledge of data analysis and statistics, and the tools, techniques and technologies of data analytics utilised in both technical and business contexts
Critically assess and evaluate business and technical strategies for data analytics
Develop and implement effective business and technical solutions for data analytics
Critically appreciate ethical and data governance issues relevant to data analytics

This course is funded under the Springboard+ initiative, click on the Springboard+ tab below for more information.

Course details

Springboard+

This course is offered under Springboard+ meaning you can join this course for free if you are currently unemployed or for a reduced cost of €650 if you are employed.

Visit the Springboard+ website to apply:

Postgraduate Diploma in Science in Data Analytics - 1 Year, Blended/Online. Applications for this programme are now closed.

Visit the Springboard+ website for information on eligibility criteria.

Applying as a non-Springboard+ Student

If you are not eligible for a place on this Springboard+ funded programme but still wish to apply, please click here.

Career Prospects

This course is designed to meet the ever-growing need for deep skills in Big Data/Analytics to fill a skills shortage in Ireland.

Companies who hired from 2022 graduates include: DTSQUARED (Data Management Consultant) Valeo (Data Management Lead), ESB (Data Analyst) SectoGMC (QA Manager), TedCastles Oil Products (Senior Business Analyst), Fidelity Investments (Senior Systems Analyst), MetLife Production (Management Analyst) Pernod Ricard (Marketing Analytics), DXC Technology (Data Analyst) , Deloitte (Artificial Intelligence Consultant).

Who is the course for?

This course is for graduates who have substantial technical,especially programming, and mathematical/statistical skills. Graduates from non-STEM disciplines (Science, Technology, Engineering, and Mathematics) that have not developed these skills will need to be able to demonstrate an aptitude for technical (programming) and mathematical problem solving.

Award and Progression

Graduates of the Postgraduate Diploma in Science in Data Analytics are awarded an NFQ Level 9 qualification. You can optionally complete the additional 30 credits required to upgrade their qualification to the MSc in Data Analytics (not included under Springboard+ - additional fee would apply).

Laptop Requirements

This programme has a BYOD (Bring Your Own Device) policy. Specifically, students are expected to successfully participate in lectures, laboratories and projects using a laptop computer with a substantial hardware configuration. A suitable configuration is 8GB of RAM (16GB are recommended); a modern 64-bit x86 processor (Intel i5 or superior); 250+ GB of available space in hard disk; WiFi card; and a recent version of Ubuntu, macOS or Windows. It is the responsibility of the student to ensure their laptop is functioning correctly and that they have full administrator rights to the machine. NCI IT does not provide support for personal devices.

The course requires internet access you will be required to ensure you have sufficient broadband speed and reliable connectivity from your place of study.

Free Laptop loan for eligible students on this course: Students who are eligible for HEA funding for this course may also be eligible for a free laptop provided on a loan basis for the duration of the programme. This will be a suitable specification machine for completion of the programme but must be returned once you have finished your course. Overall numbers of laptops available are subject to maximum numbers and no other alternatives can be offered.

Check our Student Laptop Loan page for updates on the next opening date for applications.

Course Assessment

The course will be assessed with a blend of project work and exams. This varies between modules but typically assessment is 50% continuous assessment and 50% exam. Please note that in some instances exams may take place in the daytime, evenings and at weekends.

Course Content

Semester 1

Statistics for Data Analytics
Database and Analytics Programming

Semester 2

Data Mining and Machine Learning I
Modelling, Simulation, and Optimization
Business Intelligence and Business Analytics - Elective Modules Group 1
Data Intensive Architectures - Elective Modules Group 2
Career Bridge

Semester 3

Data Mining and Machine Learning II
Data Governance and Ethics
Domain Applications of Predictive Analytics - Elective Modules Group 1
Scalable Systems Programming - Elective Modules Group 2

Note: Electives are designed to allow students gain specialised knowledge in Data Analytics related areas. Electives may have dependencies, by picking a particular elective in Semester 2, students may restrict themselves to a single choice of elective in Semester 3. For the current suite of electives, dependencies are:

Elective Modules Group 1: Business Intelligence and Business Analytics -> Domain Applications of Predictive Analytics
Elective Modules Group 2: Data Intensive Architectures -> Scalable Systems Programming

Electives will run subject to learner demand. Learners will be asked to choose their specialisation before programme commencement.

Springboard Careers Advisors will proactively support you to find relevant employment during the course or following completion of the course.

Note that all modules count towards the final award classification.

For information on the modules taught on this course view our module descriptors.

Course Delivery

This is a blended/online learning course that features Directed E-Learning activities such as live online classroom sessions and tutorials/videos on the College’s e-learning system. This allows for online class time to be interactive, practical, and focused, with theory-based content being covered outside of class time with self-paced tutorials/videos, and practical content being covered in live online classes with support from lecturers and lab assistants.

At certain limited and pre-scheduled times there will be opportunities for on-campus sessions. These on-campus sessions will also be dual delivered so students who do not wish to attend campus for these sessions will have the option of attending them online.

Indicative Schedule

Tuesday and Thursday 18.00 - 22.00

There will also be four hours self-paced learning per week on NCI’s Learning Platform weekly. This will not appear on your timetable. Career Bridge classes will be delivered one day per week in Semester 2 from 17.00 to 18.00. Day to be confirmed.

Please note that in some instances exams may take place in the daytime, evenings and at weekends.

Duration

1 Year, 3 semesters - January to May 2024, May to August 2024 and September to December 2024.

The course is expected to start in the week commencing 22nd January 2024.

Course Fee

Springboard+ Student Fees

A student contribution fee of €650 is applicable if you are in employment. No fees applicable if you are unemployed. The scheme does not cover any allowance for books and materials. See the Springboard+ tab above for further information.

If a student contribution fee is applicable this must be paid in full no later than Friday 8th of March 2024.

Non-Springboard+ Student Fees

The fee for this course is €6,500 (fees revised annually).