The goal of the UCD MSc Statistical Data Science is to train the new generation of data scientists, by empowering them with a broad range of foundational and applied skills in statistics and machine learning. On completion of the MSc Statistical Data Science, you will be able to demonstrate in-depth understanding of statistical concepts, apply advanced statistical reasoning, techniques and models in the analysis of real data and employ technical computing skills. The MSc Statistical Data Science is ideal for students interested in data science careers in industry, business, government, or to those interested in pursuing a subsequent PhD in statistics or in related areas.

The programme trains students in both applied and theoretical statistical data science, and prepares them well for a career as research data scientists. A wide variety of taught modules provides a thorough grounding in statistics and machine learning. Compulsory modules are intended to ensure that all students have appropriate statistical knowledge and experience, while optional modules provide depth and exposure to the diverse range of statistical methods and applications. In addition, students take a supervised research module where they develop an individual project that addresses a present-day statistical problem.

 

In this programme, you will learn how to design, use and interpret a variety of statistical modelling tools, combining the fundamental theory of statistics with modern computational techniques. The programme is underpinned by several thematic areas:

• Data Science: in several of our modules, you will tackle on modern real-world problems, using a variety of advanced techniques that are common in statistics and machine learning. Modules examples: Statistical Machine Learning, Data Mining, Advanced Predictive Analytics.
• Computing: you will learn how to design and implement efficient algorithms, through various data science programming languages and software that are commonly used in industry and research. Modules examples: Data Programming, Optimisation, Machine Learning with Python.
• Fundamental theory: you will cover the fundamental aspects of mathematical statistics and learn how this is used in data science to develop new methods and concepts. Modules examples: Mathematical Statistics, Multivariate Analysis, Stochastic Models.
• Communication: you will learn how to study and interpret statistical analyses, and also how to effectively communicate your conclusions. Modules examples: Technical Communication, Applied Statistical Modelling, Dissertation.

You will have the flexibility to choose your modules from a wide range of statistics topics. In addition, you will take a final dissertation module which provides you with the chance to work extensively and individually on a statistical problem, with potential industry applications or research novelty.