Foundations of Data Science: K-Means Clustering in Python
University of London
Organisations all around the world are using data to predict behaviours and extract valuable real-world insights to inform decisions. Managing and analysing big data has become an essential part of modern finance, retail, marketing, social science, development and research, medicine and government. This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Scienc
About this Course
Organisations all around the world are using data to predict behaviours and extract valuable real-world insights to inform decisions. Managing and analysing big data has become an essential part of modern finance, retail, marketing, social science, development and research, medicine and government. This MOOC, designed by an academic team from Goldsmiths, University of London, will quickly introduce you to the core concepts of Data Science to prepare you for intermediate and advanced Data Scienc
What You'll Learn
- Define and explain the key concepts of data clustering
- Demonstrate understanding of the key constructs and features of the Python language.
- Implement in Python the principle steps of the K-means algorithm.
- Design and execute a whole data clustering workflow and interpret the outputs.
Instructors
Professor Matthew Yee-King
Computing Department, Goldsmiths, University of London
Dr Betty Fyn-Sydney
Department of Computing, Goldsmiths, University of London
Dr Jamie A Ward
Department of Computing, Goldsmiths, University of London
Dr Larisa Soldatova
Department of Computing, Goldsmiths, University of London