麻豆传媒高清版

Overview

The exact content will vary by student and employer. The project will apply data processing, machine learning and AI techniques to an industrial problem and data set.

Assessment Strategy

-threshold -Equivalent to 40%.Uses key areas of theory or knowledge to meet the Learning Outcomes of the module. Is able to formulate an appropriate solution to accurately solve tasks and questions. Can identify individual aspects, but lacks an awareness of links between them and the wider contexts. Outputs can be understood, but lack structure and/or coherence.

-good -Equivalent to the range 60%-69%.Is able to analyse a task or problem to decide which aspects of theory and knowledge to apply. Solutions are of a workable quality, demonstrating understanding of underlying principles. Major themes can be linked appropriately but may not be able to extend this to individual aspects. Outputs are readily understood, with an appropriate structure but may lack sophistication.

-excellent -Equivalent to the range 70%+.Assemble critically evaluated, relevant areas of knowledge and theory to constuct professional-level solutions to tasks and questions presented. Is able to cross-link themes and aspects to draw considered conclusions. Presents outputs in a cohesive, accurate, and efficient manner.

Learning Outcomes

• Apply theoretical aspects of data science and machine learning to a real business data-set/data problem.

• Communcate the problem, method, solution and evaluation -- with references to the supporting materials -- to all interested parties.

• Formulate a machine learning/data analysis/processing solution to the identified problem.