London, United Kingdom

Data Science and Big Data Analysis (Level 2)

online course
when 26 July 2021 - 13 August 2021
language English
duration 3 weeks
credits 7.5 EC
fee GBP 2165

Data Science is an exciting new area that combines scientific inquiry, statistical knowledge, substantive expertise, and computer programming. One of the main challenges for businesses and policy makers when using big data is to find people with the appropriate skills. Students taking this module will be introduced to the most fundamental data analytic tools and techniques, learn how to use specialised software to analyse and gain insights from real-world data, and use machine learning methods for prediction and inference.

Course leader

Dr Philip Lewis

Target group

This is a level two module (equivalent to second year undergraduate). In addition to the standard UCL Summer School entry criteria, applicants will be expected to have a first year undergraduate level module in statistics. Students who have not used the R software for statistical analysis will be asked to complete a free introductory online course (approximately 10 hours), prior to the start of the module.

Course aim

Upon successful completion of this module, students will:

describe and explain key concepts, skills and tools used in the field of data science to deal with big data problems.
demonstrate how to work with different data sources and formats, and generate suitable R code to perform advanced data manipulation.
apply suitable range of techniques to explore and visualise large and complex datasets taken from a range of contexts and research areas.
construct statistical models for regression and classifications, including methods such as multivariate regression, KNN, LDA and decision tree analysis.
select appropriate methods to validate, optimise and measure the performance of different statistical methods and be able to assess, evaluate and summarise the results.

Credits info

7.5 EC
7.5 ECTS / 4 US / 15 UCL

Fee info

GBP 2165: Students who study for 6 weeks (2 modules) benefit from a built-in tuition fee discount.

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