Earning Criteria

• Complete a data science project using organisational data to address a business problem and using at least one or more analysis techniques from the Decoded Global Data Academy such as classification, regression or time series analysis. Achieve at least 50% to pass the Capstone project.
• Identifies an appropriate data question and states testable hypotheses and initial expectations. Sources relevant data and explains its application to the organisation. Fully considers data sharing issues and guidelines.
• Examines and discusses core features of the data. Uses a range of visualization methods and interprets the results. Uses a range of statistical methods to analyse data.
• Uses a range of appropriate data cleaning and preparation methods. Explains the preparation process and justifies decisions based on specific context. Shows an understanding of the implications variable transformations have on the data and the analysis.
• Use a range of analytical techniques to model and understand the data.
• Draws clear conclusions and insights from data. Explores the limitations of the model and its applicability beyond the data. Considers the data question and the hypotheses.
• The project is well-structured and has a clear narrative from beginning to end. It is comprehensible for an audience without specialist knowledge. The text is well-articulated and engaging. Visualisations are clearly labelled, adding value to the overall analysis and supporting the narrative.