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

Modules on this programme include:

• Statistics using R (10 credits): This is a year-long module which lays solid foundations in statistics, through R.
• Spreadsheet Data Analytics (5 credits): This module focuses on the use of Excel for once off analysis of existing data sets.
• Applied Database Systems (5 credits): Focuses on databases with large amounts of flat data as they appear in Big Data and Machine Learning
• Ethics and Social Responsibility in Data Analytics: Provides students with an understanding of the moral considerations that are foundational in Data.
• Advanced Statistics using R (10 credits): Focuses on non-parametric modelling, generalised linear models, and machine learning.
• Real Time Data Analytics (5 credits): Applying data analytics techniques on real-time data or data streaming with minimal latency.
• Research Methods for Data Analytics (5 credits): Introduces students to good research practice and prepares them to conduct their industry project.
• Data Visualisation (5 credits): Focuses on the effective use of visualisations to both understand data and communicate findings.
• Data Analytics Project (10 credits): Students will undertake, with appropriate supervision, an industry related data-driven project.

This course will run over 1 year, with online delivery over 3 days per week. Delivery will consist of a combination of online classes running Monday to Wednesday (daytime and evenings) and will involve a blend of "live" synchronous classes supported by additional asynchronous contact hours (videos/practical tasks), to be completed within the same week but at a time of the student’s 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 the PGDip in Science in Data Analytics or the MSc in Data Analytics programme (taught, structured or research) offered by DkIT. 

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.

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 (Programme Director)
Phone: 042 9370200 Ext 2739
Email: kevin.mcdaid@dkit.ie

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

Tim McCormac (Head of Research & Graduate Studies)
Phone: +353 (0)429370458
Email: graduatestudies@dkit.ie