20 Credits AUTUMN

Cannot be taken with: COM2004


Aims/Description: This module is intended to serve as an introduction to machine learning and pattern processing, but with a clear emphasis on applications. The module is themed around the notion of data as a resource; how it is acquired, prepared for analysis and finally how we can learn from it. The module will employ a practical Python-based approach to try and help students develop an intuitive grasp of the sophisticated mathematical ideas that underpin this challenging but fascinating subject. 

Restrictions on availability: This module cannot be taken with COM2004.

Staff Contact: BARKER JONATHAN P
Teaching Methods: Lectures, Tutorials, Laboratory work, Independent Study
Assessment: Formal Exam, Course work

Notes: This unit forms part of an accredited degree programme

Information on the department responsible for this unit (Computer Science):

Departmental Home Page
Teaching timetable

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NOTE
The content of our courses is reviewed annually to make sure it's up-to-date and relevant. Individual modules are occasionally updated or withdrawn. This is in response to discoveries through our world-leading research; funding changes; professional accreditation requirements; student or employer feedback; outcomes of reviews; and variations in staff or student numbers. In the event of any change we'll consult and inform students in good time and take reasonable steps to minimise disruption.

URLs used in these pages are subject to year-on-year change. For this reason we recommend that you do not bookmark these pages or set them as favourites.

Teaching methods and assessment displayed on this page are indicative for 2021-22. Students will be informed by the academic department of any changes made necessary by the ongoing pandemic.

Western Bank, Sheffield, S10 2TN, UK