Course Information

18-899K4: Special Topics in Signal Processing: Big Data Science




The proliferation of mobile technology, wireless sensors and social media provides a means of monitoring socio-economic activity, consumption of resources and human mobility. Recent advances in data science are now capable of coping with the technical challenges of collecting, managing and developing actionable insights from big data. Partnerships between academia, government and the private sector are at the heart of the revolution that is currently demonstrating how data is a valuable commodity and a source of intellectual property. This course will take a practical approach to solving challenges in the public and private sectors using a collection of techniques that constitute this new multidisciplinary field known as data science. A number of different themes will be explored as case studies in order to demonstrate how big data collected from a wide range of disparate sources can be combined to provide insights, drive decisions and influence policy. The course content will be structured to provide a roadmap for deploying data science techniques using case studies, reading material and previously published models. Participants will obtain hands-on experience by working on real-world datasets during assignments.

Prerequisites: Data and Inference and Applied Machine Learning Mini-Courses; Background in quantitative discipline (Engineering, Computer Science, Physics, Mathematics, Statistics); Programming.

Last Modified: 2018-01-23 5:11PM

Current session:

This course is currently being offered.

Semesters offered:

  • Spring 2018
  • Spring 2017