Data Science Foundations

Learning Outcomes

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• analyse simple unstructured datasets, and understand the challenges and risks of using standard analysis with these types of data
• write and use a simple web-scraping program
• search out and critically appraise the different types of data available for a particular task

Transferable and Generic Skills

Having successfully completed this module you will be able to:

• Use basic data science approaches to answer analytical questions
• Undertake basic data manipulation in R

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• The data science approach to modelling and interpretation

• Data availability, data access, data law (compare and contrast different countries in Europe), consent.
• Administrative Data. Sources; modes of collection, compilation and storage; quality of administrative data. Uses of administrative data in official statistics. Case study.
• Exploratory data analysis
• Basic data analysis in data science paradigm, prediction focus, train-validate-test cycle, cross-validation
• Introduction to data visualisation.
• Big Data in Official Statistics, sources, access. Data quality, information content. Relationships and causality. Timeliness. Case study. Web scraping exercise.

Depending on feasibility, teaching may be delivered face to face intensively over a week, or online using a mixture of synchronous and asynchronous online methods, which may include lectures, discussion boards, workshop activities, exercises, and videos. A range of resources will also be provided for further self-directed study.

Summative

This is how we’ll formally assess what you have learned in this module.

Referral

This is how we’ll assess you if you don’t meet the criteria to pass this module.