7 August 2020
Data Science and Big Data Analysis
This module will provide an introduction to the most fundamental data analytic tools and techniques, and will teach students how to use specialised software to analyse real-world data and answer policy-relevant questions.
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.
This module will cover classic topics in data analysis (regression, binary models, and panel data) and introduce more specialised techniques, such as classification and decision trees, clustering and pattern recognition, and dimensionality reduction.
It will cover data preparation and processing, including working with structured, key-value formatted (JSON), and unstructured data.
Dr Philip Lewis works in the Department of Cell and Developmental Biology at UCL but originally studied for his PhD in the field of High Energy Physics.
This is a level two module (equivalent to second year undergraduate). Successful completion of a first year undergraduate level module in statistics and experience of using statistical computer software is a requirement for this module. This requirement can be met by completing the R and RStudio module in Session 1.
Upon successful completion of this module, students will:
Have a sound understanding of the field of data science and have developed the ability to analyse real-world data using some of its main methods;
Be comfortable with descriptive and predictive analytics, and their application to big data problems;
Have gained a solid foundation for more advanced or more specialised study in this area.
7.5 ECTS / 4 US / 0.5 UCL
GBP 2100: Students joining us for six weeks (two modules) will receive a tuition fee discount.
GBP 1100: UCL offers accommodation in a vibrant area in the heart of London which costs approx. £1100 per 3-week Session.