Data Science & Statistical Learning

Key programme benefits to future students

The programme is designed to assist individuals with a passion for data analysis to become autonomous learners who have a creative and critical approach to data analysis. We aim to provide a learning environment that will encourage students to constructively solve data problems in real-world situations, using a variety of software, and to tailor such solutions to individual data sets as they arise.



Upon graduation, students will be able to demonstrate in-depth knowledge of the key skills required to work in the rapidly expanding field of data science. These include a knowledge of data collection methods, statistical model development, and knowledge and application of machine learning techniques. Students will develop a proficiency in several data science programming languages including R and python. Through the research focused dissertation, students will learn how to keep up to speed on the latest developments in the field of data science and demonstrate their acquired knowledge through application of modelling methodologies to challenging datasets.

Data Science and Statistical Learning



Autumn Modules

• Statistical Inference for Data Science

• Fundamentals of Statistical Modelling

• Scientific Computation

• Database Systems in Practice

• Text Analytics and Natural Language Processing



Spring Modules

• Statistical Learning

• Quantitative Research Methods for Science, Engineering and Technology

• Networks and Complex Systems

• Applied Big Data and Visualisation

• Artificial Intelligence and Machine Learning



Summer Modules

• Research Project Students will specialise their dissertation studies in one of the three sub-disciplines: Mathematics and Statistics, Electronic and Computer Engineering, or Computer Science and Information Systems

Applicants should hold a bachelor’s degree (NFQ Level 8) with at least a second-class honour, grade 2 (2:2) in Mathematics, Statistics, Physics or a relevant quantitative discipline with a strong mathematical or statistical component.



You must have and will only be considered if you have a strong foundation in mathematics from a prior programme of study, where they have excelled in their mathematical subjects.



The university may shortlist and invite you to an interview.



Previous experience of statistical programming is an advantage but is not required.

1 year full-time, on-campus.

Autumn

Graduate careers

Data science skills are some of the most highly sought after by employers both nationally and internationally. Examples of potential fields of employment include: ICT; Financial services and management consulting; Manufacturing and pharmaceuticals; Research and development roles.