Programme And Module Handbook
 
Course Details in 2022/23 Session


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Module Title LM Business Analytics
SchoolBirmingham Business School
Department Accounting
Module Code 07 36323
Module Lead Dan Herbert
Level Masters Level
Credits 20
Semester Semester 2
Pre-requisites
Co-requisites
Restrictions None
Contact Hours Lecture-24 hours
Project supervision-2 hours
Practical Classes and workshops-24 hours
Supervised time in studio/workshop-50 hours
Guided independent study-100 hours
Total: 200 hours
Exclusions
Description In this module students will be introduced to the theory and practice of business analytics. Assuming no prior knowledge students will build their personal skills in undertaking analytics tasks and their underlying of the aims, objectives and uses of analytics. The underlying rationale for and the uses of data in business situations will form the core of the module. Alongside this work students will develop practical data analytics skills. These skills will include developing the ability to undertake data analytics tasks using Python and using industry standard analytics packages to clean, process and visualise data sets. In particular students will be able to learn Tableau and undertake the Tableau Desktop Certified Associate assessment (this is voluntary and will not form part of the module assessment). Students will learn how and when to use common analytics techniques and the principles of predictive analytics.
Learning Outcomes By the end of the module students should be able to:
  • Critically evaluate the use of analytics tools to inform business decision making
  • Select, apply and evaluate common analytics techniques and implement them using appropriate software tools
  • Communicate complex data to a range of users and to critically evaluate visual data communications
  • Develop solutions to analytics problems using Python
Assessment
Assessment Methods & Exceptions Assessment: Python coding task portfolio (20%), Group Tableau data analytics and visualisation project (50%) and Individual essay (1000 words) (30%)
Reassessment: Python coding task portfolio (20%) and Individual Tableau data analytics and visualisation project with critical self-evaluation (80%)
Other
Reading List