Unit name | Applied Data Science (Teaching Unit) |
---|---|
Unit code | COMS30050 |
Credit points | 0 |
Level of study | H/6 |
Teaching block(s) |
Teaching Block 2 (weeks 13 - 24) |
Unit director | Professor. Seth Bullock |
Open unit status | Not open |
Pre-requisites |
COMS10016 Imperative and Functional Programming and COMS10017 Object Oriented Programming and Algorithms I or equivalent COMS10014 Mathematics for Computer Science A and COMS10013 Mathematics for Computer Science B or equivalent COMS20011 Data-Driven Computer Science or equivalent COMS30035 Machine Learning or equivalent Good knowledge of machine learning. Programming: Python or another major programming language (Java, C) Maths: basic linear algebra, basic statistics, some calculus, some discrete maths. |
Co-requisites |
EITHER Undergraduate students in Year 3 must choose Assessment Unit COMS30051 OR M-level students must choose the Masters Level Assessment Unit COMSM0055 OR Interactive Artificial Intelligence CDT PhD students should choose Assessment Unit COMSM0056. Please note, COMS30050 is the Teaching Unit for Applied Data Science. Undergraduate students can take this unit in either their third or fourth year, and must also choose the Assessment Unit for their year group. Interactive Artificial Intelligence CDT PhD students must chose the CDT Assessment Unit. |
School/department | School of Computer Science |
Faculty | Faculty of Engineering |
This unit introduces key data science concepts and their application to support data-driven approaches to problem solving.
The aim of this unit is to allow students to acquire fundamental skills covering the full data science pipeline, including the pre-processing, manipulation, integration, storage, exploration, visualisation and privacy.
Students will study techniques to transform raw data into advanced representations that will enable a deeper understanding of the original data:
The students will also gain practical skills in handling structured and unstructured data, gaining hands-on experience of software tools widely used in real-world settings.
On successful completion of the unit, students will:
Teaching will be delivered through a combination of synchronous and asynchronous sessions, including lectures, group work and self-directed exercises.
100% coursework.
M-level students are expected to go deeper in their analysis and reflect on the process and the steps followed.
CDT student coursework is also 100% coursework.