1. Degree
1.1. To satisfy this general aim, students will acquire key knowledge and skills in:
1.1.1. • Accessing, storing, and handling univariate and multivariate data
1.1.2. • Exploring and analysing data
1.1.3. • Visualising data
1.1.4. • Developing and comparing predictive models
1.1.5. • Formulating data-driven decision making strategies
1.2. Assessable learning outcomes:
1.2.1. On completion of this module, the student should be able to:
1.2.1.1. Select and use appropriate statistical tools to analyse data
1.2.2. Demonstrate effective use of data visualisation techniques
1.2.3. Formulate data management strategies for business data analytics
1.2.4. Critically analyse a problem domain and apply the data analytics approach to support data-driven decision making
1.3. Additional outcomes:
1.3.1. The student should:
1.3.1.1. Become familiar with the industry standard data analytics and visualisation tools
1.3.1.2. Become familiar with concepts and tools in data management
1.3.1.3. Become familiar with software development tools and approaches surrounding data analytics
1.4. Outline content:
1.4.1. Data Management
1.4.1.1. Data types and sampling methods
1.4.1.2. Storing, handling, and preparing data for analysis
1.4.1.3. Data visualisation Techniques
1.4.2. Descriptive Analytics
1.4.2.1. Descriptive Statistics
1.4.2.2. Statistical Inference
1.4.2.3. Exploratory Data Analysis
1.4.3. Predictive Analytics
1.4.3.1. Regression Modelling
1.4.3.2. Machine Learning
1.4.4. Prescriptive Analytics
1.4.4.1. Programming for data analytics
1.4.4.2. Recommendations and solutions development