Upskill for the Big Data age with our focused data science course.
Data science spans information and computational science, mathematics, and statistics. It seeks to identify and understand phenomena as captured in structured or unstructured data.
Train in the data science techniques that are revolutionising the way we use data. Learn how to handle large datasets and extract meaningful insights from data.
Explore the benefits these techniques can bring to businesses across all sectors. Generate data-driven predictions and recommendations to optimise processes, workflows, and equipment use.
The credits you earn on this course count towards our Masters in Petroleum Data Management, also available to study online.
What will I study?
You’ll gain an introduction to data science and study common data science techniques. You’ll also consider the challenges and implications for data managers.
You’ll cover:
- Data analytics
- Data mining
- Challenges and solutions for large datasets, or ‘big data’
- Real-time data analysis
- Machine learning
- Artificial intelligence
- Neural networks
- Data classification, pattern-recognition and cluster analysis
- Uncertainty quantification
- Data visualisation
- Data integration models for making predictions and recommendations
Data science is increasingly important in many different areas. You’ll explore wide-ranging examples, from Natural Language Processing (eg, analysing Tweets and Facebook posts), to Astro-Archaeology.
By the end of this course, you will be able to…
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Handle large datasets, or ‘big data’.
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Conduct cluster analysis of data.
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Identify and understand phenomena captured in structured or unstructured data.
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Carry out data analysis.
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Generate data-driven predictions that aid business optimisation.
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Produce reports based on data analysis.
How will I study?
This is an 11-week course, delivered entirely online. It’s assessed online too. You can study with us anywhere in the world and manage your study hours to suit you.
The course is taught at Masters level by experienced data scientists from the School of Natural and Computing Sciences. As well as guiding you through the course, they’ll be on hand to discuss your work with you using online forums.
Your course is delivered through MyAberdeen, our Virtual Learning Environment (VLE). It’s also available as an app, so you can study on computer, smartphone and tablet 24/7.
Your course features a range of resources, including:
- videos
- online lectures
- interactive lecture material
- quizzes
- projects
- reading materials
- the online resources of our award-winning Sir Duncan Rice Library
Where will this take me?
You’ll earn 15 credits at Masters level (SCQF Level 11) with this course. You can use these credits towards our:
Masters in Petroleum Data Management
- Designed in partnership with industry
- Study part-time online or full-time on campus
Careers
Companies today need data scientists who are not only highly skilled in a wide range of statistical and data analysis tools, but who can go far beyond classical statistics and machine learning to gain real insights from data.
This course provides the practical training you need to extract those insights. You’ll learn to create data-driven solutions to problems across many disciplines and industries.
Your employer or professional institute may recognise this course for Continuing Professional Development (CPD). Talk to your employer or institute to find out more.
Your course coordinator
Professor Marco Thiel
Marco is an applied mathematician with a background in theoretical physics and dynamical systems. He works in Applied Mathematics and Physics at the University. Marco specialises in applying mathematical modelling and data analysis to a multitude of applications, from Alzheimer’s disease and population dynamics to the movement of newborns and the mating behaviour of fireflies.
View Marco’s profileThis course has no formal entry requirements. You decide if it’s suitable for you.
The course is delivered at Masters level. At this level, you’d usually have at least:
- a 2:2 (second-class) degree
- or relevant experience that supports this level of study.
You do not need a science or maths degree to take this course. It’s open to students and professionals across all academic backgrounds.
Apply for this course
