Institute and Faculty of Actuaries Data Science Certificate

The Institute and Faculty of Actuaries (IFoA)’s Data Science Certificate, jointly accredited by the Web Science Institute at the University of Southampton, offers members a practical introduction to the concepts, tools and techniques of data science within an actuarial context.
Watch our video to hear Dame Wendy Hall, Executive Director of the Web Science Institute, talk more about why actuaries will benefit from this course:
The course will help actuaries make sense of the management of large quantities of data and other emerging challenges in today’s workplace. It will also bring together a wide range of issues actuaries should consider with regards to data science, including ethics, professionalism, regulation, and public interest.
In addition, it will help actuaries better understand the work of data scientists, who they will increasingly work alongside.
The Data Science Certificate is a part-time, online course, with no requirement for any minimum programming skills. It will require approximately 10 hours of study per week, across an eight-week period, with an additional two weeks to complete the final assignment.
The delivery will be through an online virtual learning environment, supported by the Southampton Data Science Academy (SDSA), and on enrolment participants will become students of the Academy.
David Tudor-Griffith was part of the first IFoA Data Science Certificate cohort. Read about his experience on the course here. See all data science blogs on the IFoA website.
The Data Science Certificate will highlight many of the issues actuaries should consider when working in multi-disciplinary teams on data science related projects.
You will also learn how some of these tools have been applied across the core actuarial domains; using practice area specific case studies. 
The Data Science Certificate is designed around six manageable modules, each with specific learning materials and academic support.
These modules are:
  • Introduction to Data Science, Data Management and Processing
  • Data Analysis and Introduction to Machine Learning
  • Data Visualisation and Communication
  • Further Analysis and Artificial Intelligence
  • Good Practice and Responsible AI
  • Future Directions
Learning outcomes
At the end of this course you will be able to:

  • Understand core concepts in data science and how they relate to AI and machine learning.
  • Retrieve, process and manage relevant data in a range of formats.
  • Analyse relevant datasets with state-of-the-art tools and techniques.
  • Identify opportunities to apply business solutions with the latest Machine Learning and Artificial Intelligence technologies in an actuarial context.
  • Provide insights about the legal, ethical and technical implications of using big data and AI in an actuarial context.
The course includes technical exercises which will allow participants to work through practical examples using data science tools. There will also be additional, non-assessed technical exercises that will also allow participants to test out some techniques that may interest them personally.


Rob Blair

Rob is Visiting Fellow at the University of Southampton’s School of Electronics and Computer Science. He holds an MSc Information Systems from the University of East Anglia and an MSc Web Science from the University of Southampton. Qualified to teach Physics, Mathematics and Computer Science, Rob is a highly-experienced classroom teacher and online tutor specialising in data science.


Manuel León Urrutia

Dr. Manuel León Urrutia is Research Fellow in the Web and Internet Science research group of the Electronics and Computer Science department of the University of Southampton. Manuel is specialised in learning technologies, with experience in learning design and research interests in MOOCs and learning analytics. Prior to joining the Computer Science department in 2012, he worked for 6 years as an editor in a publishing company, and 6 more years as a language teacher in the University of Southampton. Manuel currently has an academic, senior tutoring and learning design role in the Southampton Data Science Academy.

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