On successful completion of this programme the learner will be able to :
|
Description
|
|
Identify, clean, integrate, select, transform, and mine different types of datasets in order to evaluate knowledge and present novel insight.
|
|
Design, implement, evaluate and document algorithmic solutions that demonstrate use of state of the art processes, methodologies, tools and techniques that efficiently solve a variety of complex problems.
|
|
Utilise advanced statistical analysis, modelling, data mining and machine learning tools and techniques to analyse and derive insight and value from data in an applied context.
|
|
Adopt appropriate professional, ethical, legal, security and privacy principles in the construction and implementation of data science solutions.
|
|
Effectively visualise and communicate the results of analysis to both technical and non-technical audiences in a professional setting.
|
|
Critically and effectively analyse problems through both independent and collaborative efforts in order to develop solutions and provide information and insight to meet business requirements as part of a professional team.
|
|
Use problem solving and analytical thinking techniques, communication, and interaction skills to support decision making in a variable and unfamiliar learning context.
|
Stage 1 / Semester 1
|
|
|
|
|
|
|
|
|
|
|
Stage 1 / Semester 2
|
|
|
|
|
|
|
|
|
Stage 2 / Semester 1
|
|
|
|
|
|
|
|
|
Stage 2 / Semester 2
|
|
|
|
|
|
|
|
|
Stage 3 / Semester 1
|
|
|
|
|
|
|
|
|
|
|
Stage 3 / Semester 2
|
|
|
|
|
|
|
Stage 4 / Semester 1
|
|
|
|
|
|
|
|
|
|
|
Stage 4 / Semester 2
|
|
|
|
|
|
|
|
|
