- Demonstrate in-depth knowledge of the key skills required by a practicing data analyst, including data collection methods, statistical method development, knowledge and application of machine learning techniques
- Ability to present technical material at a level appropriate for any audience
- Proficiency in data science programming in R
- The ability to create scientific visualisations to explore, summarise, and interpret complex datasets
- Approach problems in an analytical, precise and rigorous way
- Model a broad variety of real-world problems in a statistical framework
This course is available through the following application route(s)
This online-delivered course is designed to provide you with the essential skills of the modern data scientist, including data handling and programming, statistical analysis, and machine learning methods. There is an increasing demand for graduates with these valuable skills in a wide range of industries, and currently a shortage of qualified graduates.
In this course students will learn data analysis and programming techniques through online taught modules. There are no lectures to attend in person as the courses are delivered completely online by staff of the School of Mathematics & Statistics. Students are required to take in-person examinations at the end of the second (Spring) trimester. All other assessments will be completed online.
Students will be given videos, online demonstrations, and interactive games to enhance their learning, with regular feedback and interaction with course tutors. This provides flexibility to students who can learn wherever they like at a pace that suits them. Students will be assessed through a combination of homework assignments and written exams to assess mathematical skills. Students are required to take in-person examinations at the end of the second (final) trimester of the programme. All other assessments will be completed online.
Students who successfully complete the diploma and wish to continue their studies may be eligible to progress to the MSc in Data Science (F275)
For detailed information about the programme email dataanalyticsonline@ucd.ie with any queries.
- There is a huge ongoing growth in demand for graduates with these valuable skills in a wide range of industries, and currently a shortage of qualified graduates.
- Students will be given videos, online demonstrations, and interactive games to enhance their learning, with regular feedback and interaction via course tutors through the UCD website.
About This Course
Below is a list of all modules offered for this degree in the current academic year. Click on the module to discover what you will learn in the module, how you will learn and assessment feedback profile amongst other information.
Incoming Stage 1 undergraduates can usually select an Elective in the Spring Trimester. Most continuing undergraduate students can select up to two Elective modules (10 Credits) per stage. There is also the possibility to take up to 10 extra Elective credits.
| Trimester | Credits | |||
|---|---|---|---|---|
Stage 1 Core Modules |
STAT30280 | Inference for Data Analytics (online) | 5 | |
Stage 1 Core Modules |
STAT40720 | Introduction to Data Analytics (Online) | 5 | |
Stage 1 Core Modules |
STAT40730 | Data Programming with R (Online) | 5 | |
Stage 1 Core Modules |
STAT40750 | Statistical Machine Learning (online) | 5 |
Data Scientists are in strong demand from industry; those who are successful in completing the course are highly employable in fields as diverse as pharmaceuticals, finance and insurance, as well as cloud computing. Some examples of prospective employers include ICT companies (e.g., Google, eBay, Facebook, Amazon, Paddy Power); the pharmaceutical industry (e.g., Janssen, Merck, GSK); and the financial services industry (e.g., Bank of Ireland, AXA, EY, Accenture, Deloitte)
For entry to the Professional Diploma in Data Science (LEVEL 9), students must have obtained an undergraduate (NFQ Level 8 ) or masters degree to standard 2:1 in a subject with some quantitative elements.Those with a lesser qualification award and/or no numerate subject degree, but with substantial industry experience related to the area, or relevant professional qualifications, will also be considered on a case by case basis. A rough guide to the mathematics we expect you to know on entry is available here: Self Assessment Quiz
Applicants whose first language is not English must also demonstrate English language proficiency of IELTS 6.5 (no band less than 6.0 in each element of the Academic version), or equivalent.
You may be eligible for Recognition of Prior Learning (RPL), as UCD recognises formal, informal, and/or experiential learning. RPL may be awarded to gain Admission and/or credit exemptions on a programme. Please visit the UCD Registry RPL web page for further information. Any exceptions are also listed on this webpage.
Part Time option suitable for:
Domestic(EEA) applicants: Yes
International (Non EEA) applicants: Yes
How to Apply
General application route(s) for Irish/UK/EU applicants* for International (non-EU) applicants* to Data Science:
| ROWCLASS | Apply to |
|---|---|
| showAudience-audienceEU showAudience-audienceInt | F274 Data Science Professional Diploma Part-Time Commencing September 2025 Graduate Taught |
* you can change options at the top of the page