ITO5149 · Applied data analysis

Overview

This unit aims to provide you with the necessary analytical and data modelling skills for the roles of a data scientist or business analyst. You will be introduced to established and contemporary Machine Learning techniques for data analysis and presentation using widely available analysis software. You will look at a number of characteristic problems/data sets and analyse them with appropriate machine learning and statistical algorithms. Those algorithms include regression, classification, clustering and so on. The unit focuses on understanding the analytical problems, machine learning models, and the basic modelling theory. You will need to interpret the results and the suitability of the algorithms.

Offerings

Assessment

The Handbook does not list a final examination among the assessment items. That is not a guarantee there is none.

Assessment details may change. Please refer to the assessment information in Moodle closer to the start of the teaching period.

Requisites

Learning outcomes

1. Analyse data sets with a range of statistical, graphical and machine-learning tools;
2. Evaluate the limitations, appropriateness and benefits of data analytics methods for given tasks;
3. Design solutions to real world problems with data analytics techniques;
4. Assess the results of an analysis;
5. Communicate the results of an analysis for both specific and broad audiences.

Workload

A minimum of 144 hours over the 6 week teaching period should be used to complete assignments, participating in discussions, private study and revision.

Student experience, not official rules. Nothing here changes what the Handbook says.