UWI's MSc. Data Science

• Course Code: COMP 6501
  Course Name: Research Methods, Entrepreneurship, and Intellectual Property
  Description: This course introduces students to three important non-technical topics: Research Methods, Entrepreneurship, and Intellectual Property. These broad non-technical skillsets are vital for students seeking to start businesses or engage in scientific research.
• Course Code: COMP 6925
  Course Name: Applied Operations Research
  Description: The purpose of this course is to study the basic tools for quantitative methods for decision-making. The emphasis is on solution methods and strategies. The course introduces the student to a wide variety of tools used in the decision making process and demonstrates the application of these tools on real-world examples.
• Course Code: STAT 6105
  Course Name: Probability and Statistical Methods for Data Analytics
  Description: Data Analytics is the process of examining data with the purpose of drawing conclusions and discovering useful information. In this science, probability theory provides the foundation for many of the fundamental data analyses and modelling techniques widely used today. Statistical methods, such as hypothesis testing, are used to draw conclusions about data and provide a foundation for more sophisticated data analysis techniques. Viewing questions about data from a statistical perspective allows data scientists to create more predictive algorithms to convert data into knowledge.
• Course Code: STAT 6106
  Course Name: Statistical Inference for Data Analytics
  Description: The course is aimed at those whose future careers will involve a heavy use of statistical methods and at the same time fulfil the required knowledge of mathematical statistical inference needed at the postgraduate level. Statistical inference provides a foundation for sophisticated data analysis techniques. It is essential for data analysts to have a strong understanding of statistical inference before applying these techniques.
• Course Code: COMP 6930
  Course Name: Machine Learning and Data Mining
  Description: With the rise of data science and big data fields, machine learning has gained further recognition as the key driver behind the successful advance of these fields. However, many recent entrants to the field can only utilize the variety of machine learning algorithms as black boxes. This course aims to empower students to effectively use and understand the primary approaches so as to be able to modify them for specific uses. Our focus is less on theory and more on practice. Students engage in hands-on implementation of some of the fundamental algorithms such as predictive modeling and clustering applied to real, open-ended problems. While most of the course focuses on machine learning, we also have a few lectures on text/data mining algorithms.
• Course Code: COMP 6940
  Course Name: Big Data and Visual Analytics
  Description: Big data is data that is generally too large to fit into the analyst’s computer. Since storage and networking are getting less costly as well as faster, big data can be transported easily to a destination where analysis needs to be done. Insights and business value can be drawn from big data. It is also useful for policy makers e.g. Government. The course aims to provide a broad understanding of big data sets, emerging technologies for these large data sets and methods of analysis of big data.
• Course Code: COMP 6940
  Course Name: Research Project
  Description: The objective is to allow students to think independently and provide a unique contribution to their field. Examples of past projects can be found here: https://lab.tt/index.php/theses/