Course summary

What is special about this course? Are you interested in making an impactful and effective contribution to business through data science? If so, this new MSc Applied Data Analytics will allow you to develop your skills and knowledge in data analytics techniques and evaluate their relevance and validity. You will learn key data science skills using freely available software. Core subjects will cover fundamental theories, ethical considerations and industry-standard techniques, while optional modules will allow you to focus on specific applications. The range of options include business, computational, and environmental themes. As part of the environmental options, you will gain experience with GIS software and spatial analysis, while in the business-themed options the focus is on business decisions and company culture – can you help it move toward data-driven decision-making? The computational theme has an emphasis on data engineering and machine learning. This part-time course is delivered online, allowing you the flexibility to fit your studies around your personal and professional commitments and tailor your option choices to suit your specific areas of interest. This course may also be of interest to companies wishing to use it as continuing professional development for their employees. This course may also be of interest to companies wishing to use it as continuing professional development for their employees. Further information on the course, including more detail about the individual modules, can be found on our website at: https://induction.uhi.ac.uk/STE/msc-ads-student-handbook/index.html Special features ◾Flexible optional themes (business, computational and environmental) ◾Learn to apply a wide range of data analytics techniques and evaluate their relevance and validity ◾Make an immediate and effective contribution to an organisation through data science ◾Study current ethical issues in data science and their application to an organisation How long will my course last? ◾Part-time: 2-3 years @ approximately 15-20 hours per week ◾Part-time (modular): 14 weeks per module @ approx 14 hours a week Number of hours per week indicates the total number of hours you should dedicate to the course, which includes time spent in lectures and your own time spent on individual study and research.