Course Description

Welcome to the Big Data Capstone Project, a cutting-edge course designed to put your data science skills to the test in a real-world setting. This advanced-level course is the culmination of the Big Data MicroMasters program and provides an unparalleled opportunity to apply your knowledge to a medium-scale data science project.

In this course, you'll work with actual organizations and stakeholders on genuine datasets, allowing you to bridge the gap between theory and practice. You'll be challenged to plan and execute a substantial project, demonstrating your ability to work autonomously and take initiative.

What You'll Learn

• Practical application of data science techniques, principles, and theories
• Project planning and execution in a data science context
• Autonomous work and initiative-taking skills
• Identification and analysis of social and ethical concerns in data science
• Advanced communication skills using online collaborative technologies
• Effective presentation of project design, methodologies, and outcomes

Prerequisites

To succeed in this capstone project, students should have completed the following courses in the Big Data MicroMasters program:

1. Programming for Data Science
2. Computational Thinking and Big Data
3. Big Data Fundamentals
4. Big Data Analytics

Course Content

• Dataset overview, selection, and ethical considerations
• Data cleaning and preprocessing techniques
• Regression analysis and model fitting
• Classification methods and feature selection
• Performance evaluation of classifiers
• Project design and planning
• Ethical frameworks in data science
• Communication and presentation of data science projects

Who This Course Is For

• Aspiring data scientists looking to gain practical experience
• Professionals seeking to transition into big data roles
• Students aiming to complete their Big Data MicroMasters program
• Anyone looking to apply their data science knowledge to real-world problems

Real-World Applications

The skills acquired in this course are directly applicable to various industries and roles:

1. Data-driven decision making in business and organizations
2. Developing and implementing data science solutions for complex problems
3. Ethical considerations in data handling and analysis
4. Effective communication of technical findings to diverse audiences
5. Project management in data-centric environments
6. Solving real-world challenges using big data techniques

Syllabus

1. Dataset overview, data selection and ethics
   • Understanding ethical issues in big data projects
   • Applying ethical analysis to scenarios
   • Describing ethical approaches
2. Exam (timed, proctored)
   • Covering content from the first four courses in the Big Data MicroMasters program
   • Topics include code structure, testing, variable types, graphs, big data algorithms, regression, and ethics
3. Project Task 1: Data cleaning and Regression
   • Data cleaning and preprocessing
   • Creating computer code for data handling
   • Fitting and evaluating regression models
   • Applying regression models for predictions
4. Project Task 2: Classification
   • Building and analyzing classifiers
   • Designing feature selection schemes
   • Evaluating classifier performance

By enrolling in this course, you're not just completing a program – you're taking a significant step towards becoming a proficient data scientist, equipped with the skills and experience to tackle real-world big data challenges.