Advanced Data Analysis and Concepts in Machine Learning

Advanced Statistical Analysis and Machine Learning

OBJECTIVES

  • Reinforce expertise in advanced statistical analysis and probabilistic methods.
  • Learn some key principles involved in machine learning.
  • Reinforce modelling skills in using some advanced functionality and VBA macros.

DESCRIPTION

  • Overview. This course covers some key topics in advanced statistics and data analysis. It also introduces some of the key principles and methods used in machine learning. It focusses on the overall concepts, as well as on specific methods that can be implemented or demonstrated using Excel and VBA.
  • Practical Work and Exercises. Readers are expected to build simple examples for themselves as they follow the text. The course also contains downloadable data sets or simple models that allow a reader to do this practical work without having to enter large sets of data or repeat previous steps.

KEY TOPICS

  • Reinforcement of Advanced Statistics. In-depth review or recap of concepts and methods in single and multi-variate statistics and their calculations and Excel functions, as well as key ideas in probability and risk assessment. Tree-based decision-making and real options· Conditional probability · Bayesian analysis · Value of test-based information.
  • Introduction to Machine Learning. Machine learning concepts · Model calibration using optimisation ·  Value of information · Entropy · Cluster analysis · Optimal decision trees and information sequencing · Reinforcement learning · Other machine learning algorithms and methods