Data Scientists who require code and algorithms to run faster than can be achieved using standard R or python routines.
Data Programming with C
Overview
| Module Code | STAT40780 |
| Module Title | Data Programming with C |
| Subject Area | Data Science |
| Credits | 5 |
| NFQ | 9 |
| EFQ | |
| Start Date | 19th May 2025 |
| Duration | 12 Weeks |
| Time | N/A |
| Mode of Delivery | Online |
| Course Leader | Michael Salter-Townshend |
| Fee | Full Fee: €875 *Subsidised Fee: €175 *80% fee subsidy for eligible learners. (See Below) |
| Application Deadline | 9th May 2025 |
The module covers the programming with data using the languages C and C++, with a particular focus on incorporating such code into the R statistical environment. Students will learn the structure of both languages and how commands can be called from R via the Rcpp and inline packages. This enables a very large speed gain over traditional R commands, and is especially useful for large data sets.
- On successful completion of this micro-credential, you will be able to:
Write code in both C and C++ and call such code into R - Use the Rcpp and inline packages to export variables from C into R and vice-versa
- Use advanced features of the packages to work with large data objects and perform complex data manipulation
C and C++ basics and syntax, the Rcpp and inline R packages.
You will gain the ability to write data science code that is many orders of magnitude faster to run. This is especially important when working with big data or complex models.
Video lectures posted each week that walk through module content, blending theory with example exercises.
Practice problem sheets to enable self-assessment of learning outcomes.
All content delivered using the VLE which includes a monitored discussion forum with topics created for each weeks lecture material and each problem set.
You should already be familiar with the R programming language.
Programming exercises and short projects – 40%
Exam (online) – 60%
Post-assessment group/class feedback will be provided.
Prof Cert in Data Science
Please note: Learners can avail of only one form of funding per application.
Micro-Credentials Learner Fee Subsidy-Human Capital Initiative Pillar 3
The HCI Pillar 3 Micro-credential Learner Fee Subsidy has been introduced to enable more learners to address critical skills gaps and engage with lifelong learning through micro-credentials. The HCI Pillar 3 Micro-credential Learner Fee Subsidy is funded by Higher Education Authority (HEA) and the Department of Further and Higher Education, Research, Innovation and Science.
HCI Micro-credential Learner Fee Subsidies are available on identified micro-credentials only and in fixed numbers from March 2024 until October 2025.
Please see Eligibility Criteria for further information.
On successful completion of this micro-credential, you will receive credits as per the European Credit and Transfer System. These credits are recognised by the awarding institution as credits aligned to learning completed at postgraduate level.
If you have any questions about this micro-credential, or would like to speak to a UCD staff member, please contact (opens in a new window)microcredentials@ucd.ie.