Data Analytics for Finance

Course information for CPA Ireland's elective subject at the Strategic Level

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Why Data Analytics for Finance?

Through the study of this subject, students will develop highly sought-after analytical skills such as capturing, interpreting and reporting on big data.

Method: The course will be delivered through livestreamed lectures once a week, with class notes available in advance. Students will have the option of attending the livestreamed sessions or watching them at a later date. Students will have the option to take a mock exam in advance of the April diet of examinations.

Location: Online via Canvas Learning Management Systems. Once you are enrolled you will be contacted with your new Canvas account details before the course starts.

Time: Every Monday at 6:00PM.

Dates: 14 October 2024 - 7 April 2025.

Cost: €500.00

 
  • The course will cover the underlying mathematical concepts and technology involved in Data Analytics, and will focus on the application of these concepts in the domain of Business and Finance. 
  • The tutor will use tools such as Excel and RStudio to demonstrate key concepts, however students are not expected to create code and will not be examined in this area.
  • Students should have a base knowledge of Excel when starting this course.

Learning Outcomes

On completion of this module, students will achieve the following learning outcomes:

  • Discuss the strategic processes, benefits and challenges of applying Data Analysis techniques to improve decision making for competitive advantage
  • Apply statistical techniques, including regression and time series, to business datasets and interpret statistical results for various user groups.
  • Describe the key concepts underpinning various supervised and unsupervised machine learning techniques 
  • Interpret outputs from a variety of Data Analytics software tools, such as Excel, R and Python, and discuss the risks in making business recommendations from these outputs
  • Evaluate the benefits and risks of utilising machine learning techniques in a variety of business financial activities. 
  • Assess data protection, data privacy and other ethical issues associated with the utilisation of large corporate datasets   

Syllabus Includes:

  • Strategic Data Management in Finance
  • Exploratory Data Analysis
  • Statistics for Big Data
  • Dimension Reduction
  • Regression and Big Data
  • Forecasting Techniques and Application
  • Machine Learning
  • Model Evaluation
  • Data Ethics and Legal Considerations