Introductory Data Science for Innovation (995N1)

15 credits, Level 7 (Masters)

Autumn teaching

In a digitalised society, learning from data has become increasingly important to address policy questions and generate business intelligence in a timely and effective manner. The “Introductory Data Science for Innovation” module provides you with cutting-edge skills (e.g. text-mining, sentiment analysis, infographics) to generate evidence for decision making in policy and management contexts.

Building on a diverse set of data sources (e.g. publications, patents, social media, research funding, firm-level data), you will acquire analytical and visualisation expertise to explore the innovation process at multiple levels (e.g. organisations, regions, nations), but also to interpret critically the findings of the analysis. Lectures and seminars are complementary: Lectures provide you with the conceptual and theoretical base to get acquainted with data science approaches to study innovation, while a series of computer-based seminar sessions apply these approaches to real examples in policy and management.

Teaching

100%: Practical (Workshop)

Assessment

30%: Coursework (Group presentation)
70%: Written assessment (Report)

Contact hours and workload

This module is approximately 150 hours of work. This breaks down into about 36 hours of contact time and about 114 hours of independent study. The University may make minor variations to the contact hours for operational reasons, including timetabling requirements.

We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We’re planning to run these modules in the academic year 2022/23. However, there may be changes to these modules in response to COVID-19, staff availability, student demand or updates to our curriculum. We’ll make sure to let our applicants know of material changes to modules at the earliest opportunity.