Explore and evaluate datasets using descriptive statistical analyses.
Apply statistical analysis to appropriate datasets and critique the limitations of these models.
Utilise current software tools and languages to produce and document result sets from existing data.
Develop a machine learning strategy for a given domain and communicate effectively to team members, peers, and project stakeholders the insight to be gained from the interpreted results.
Implement a range of classification and regression techniques and detail / document their suitability for a variety of problem domains.
Critically evaluate the performance of Machine Learning models, and propose strategies to optimize performance.
Discuss the concepts, techniques, and processes underlying data visualization to critically evaluate visualization approaches with respect to their suitability for different problem areas.
Programmatically Implement graphical methods to identify issues within a data set.
Engineer new feature selection in data with the goal of improving the performance of machine learning models.
