Data Mining for Business Analytics

Aim

To provide learners with practical experience in developing analytical tools that provide

Indicative content

Data mining algorithms and their application on business analytical problems including clustering, association rules, classification and machine learning, Statistical methods for evaluating the predictive accuracy of data mining models, Visual approaches for presenting and evaluating predictive models and their results, Contemporary issues relating to data mining and its application within business analytics, Communication strategies for conveying meaning from analytical results to a target audience, Statistical programming tools and techniques for creating and evaluating predictive and explanatory models, insight and understanding of business performance based on data mining methods.

Learning Outcomes

On successful completion of this course, the learner will be able to:

1. Create a range of explanatory and predictive models that support fact-based management and decision making
2. Critically assess analytical results and convey their meaning to a target audience
3. Use statistical programming tools to perform a variety of commonly applied data mining functions on business data
4. Apply visualisation techniques for evaluating predictive models and the presentation of analytical results
5. Identify and explain appropriate data mining methods for tasks relating to business analytics
6. Critically assess the quality of predictive models using statistical methods