Applied Data Analytics

(3 Credit Hours) · Undergraduate

This course will examine current trends in data science, including those in big data analytics, and how it can be used to improve decision-making across different fields, such as business, economics, social and political sciences. We will investigate real-world examples and cases to place data science techniques in context and to develop data-analytic thinking. Students will be provided with a practical toolkit that will enable them to design and realize a data science project using statistical software Module Description: This module provides an introduction to modelling using differential equations, via the MATLAB software system. In addition to modelling, a core part of the course is to introduce good software design principals in MATLAB, through the use of functions. The course also covers exploratory data analysis, and initial data modelling tasks in MATLAB, to provide a contrast to the differential equations approach. Learning Outcomes Understand matrix manipulation using MATLAB Explain key MATLAB concepts: function design, element-wise operations, and logicals Design difference equations for modeling state changes Develop ODE models in MATLAB, including Newton's Law of Cooling Design simulation models using Simulink Introduce data science approaches in MATLAB..