The Big Data Capstone project will give you the chance to demonstrate practically what you have learned in the Big Data MicroMasters program including:

• How to evaluate, select and apply data science techniques, principles and theory;
• How to plan and execute a project;
• Work autonomously using your own initiative;
• Identify social and ethical concerns around your project;
• Develop communication skills using online collaborative technologies.

Dataset overview, data selection and ethics
Understand ethical issues and concerns around big data projects;Describe how ethical issues apply to the sample dataset;Describe up to three ethical approaches;Apply ethical analysis to scenarios.

Exam (timed, proctored)
The exam will cover content from the first four courses in the Big Data MicroMasters program, including the Ethics section of this capstone course, DataCapX. Itwill include questions on topics such as code structure and testing, variable types, graphs, big data algorithms, regression and ethics.

Project Task 1: Data cleaning and Regression
Understand the basic data cleaning and preprocessing steps required in the analysis of a real data set;Create computer code to read data and perform data cleaning and preprocessing;Judge the appropriateness of a fitted regression model to the data;Determine whether simplification of a regression model is appropriate;Apply a fitted regression model to obtain predictions for new observations.

Project Task 2: Classification
Build classifiers to predict the output of a desired factor;Analyse learned classifiers;Design a feature selection scheme;Design a scheme for evaluating the performance of classifiers.