Introduction to Data Science - 2019 entry

***DATA SCIENCE AND DATA SCIENCE WITH BUSINESS STUDENTS ONLY***

In this module you will learn about the broad and fast-moving field of data science. You will be introduced to the core competencies and application areas associated with data science, including data handling & visualisation, machine learning, statistical modelling, social network analysis, text mining, machine vision and high-performance computing. You will also explore the ways in which data science is transforming business and society. Practical exercises, individual study and group work will consolidate your learning and provide the foundations for later study.

Pre-requisite modules: None.
Co-requisite modules: None.

This module is a core module for MSc Data Science (Professional) students.

This module provides the foundations for the MSc Data Science (Professional). It will cover the breadth of data science to equip students with the context and vocabulary to support more detailed study in future modules. Topics will include: The Data Revolution, Exploring Data, Machine Learning & Statistics, Data in Society & Business, Social Networks & Text Analysis, High Performance Computing & Data Architectures, Machine Vision, Information Security.

Most taught content will be delivered in an intensive one-week residential block, including lectures and practical work. Lectures will be accompanied by data analysis exercises and seminar discussions. A series of guided practical exercises will develop your skills in programming (in Python and/or R), data handling and visualisation. You will undertake individual and group presentations exploring the potential impact of data science in your own organisation and in wider society. Guest lectures from industrial data science practitioners and additional training opportunities will enrich the core  syllabus. Subsequent to the initial teaching week, you will complete the module through individual study and coursework, supported by the module staff.

Assessment will include assessed practical exercises, individual and group presentations, and an investigation of a chosen aspect of data science.

On successful completion of this module you should be able to:

Module Specific Skills and Knowledge

Discipline Specific Skills and Knowledge

Personal and Key Transferable / Employment Skills and Knowledge

Topics (with associated exercises and seminar discussions):

• The Data Revolution
• Exploring Data with R and/or Python
• Machine Learning & Statistics
• Data in Society & Business
• Social Networks & Text Analysis
• High Performance Computing & Data Architectures
• Machine Vision
• Information Security

Deferral – if you miss an assessment for certificated reasons judged acceptable by the Mitigation Committee, you will normally be either deferred in the assessment or an extension may be granted. The mark given for a reassessment taken as a result of deferral will not be capped and will be treated as it would be if it were your first attempt at the assessment.

Referral – if you have failed the module overall (i.e. a final overall module mark of less than 50%) you will be required to re-take some or all parts of the assessment, as decided by the Module Convenor. The final mark given for a module where re-assessment was taken as a result of referral will be capped at 50%.
 

Basic reading:

ELE: http://vle.exeter.ac.uk/

Web based and Electronic Resources:

Other Resources:

Reading list for this module: