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Module Content:Ìý

This 1st year undergraduate module covers mathematical foundations and fundamental statistical concepts required for developing a broad range of data and information processing skills. The module is aiming to prepare students, including those who had limited opportunities to study the subjects prior, to frame problems in the domain of information studies, reason and propose solutions around these using mathematical and statistical methods. The module is intended to prepare students to take on subjects such as Machine Learning, Natural Language Processing, Graph Databases and Logic. ÌýStudents will have good maths competency but may not have A level maths or equivalent.Ìý

Learning Outcomes:Ìý

On successful completion of this module, students will be able to:

• Summarise, visualise and present statistical data effectively.Ìý
• Design experiments and conduct statistical analysisÌý
• Apply mathematical foundations and algorithmic principles in the domain of Information StudiesÌý
• Problem-solve real-life phenomena using mathematical modelling and data analysis.Ìý

Delivery Method:Ìý

A combination of teaching and learning methods will be used: lectures and computing laboratory work, putting more emphasis on application of theoretical knowledge to address real-life problems.Ìý

Additional Information:Ìý

Weekly feedback on problem-based tutorial sheet work.  Lab-based practical work with peers and teaching staff.Ìý

Brief overview of indicative readings:Ìý

• Chatfield, C., 2018. Statistics for technology: a course in applied statistics. Routledge.Ìý
• Anton, H., Bivens, I.C. and Davis, S., 2021. Calculus. John Wiley & Sons.Ìý
• Ross, S.M., 2017. Introductory statistics. Academic Press.Ìý