RES.LL-005 | January IAP 2020 | Undergraduate

Mathematics of Big Data and Machine Learning

Instructor Insights

Course Overview

This page focuses on the 8-lecture course D4M Signal Processing on Databases as it was taught by Dr. Jeremy Kepner in Fall 2012.

Search, social media, ad placement, mapping, tracking, spam filtering, fraud detection, wireless communication, drug discovery, and bioinformatics all attempt to find items of interest in vast quantities of data. This course teaches a signal processing approach to these problems by combining linear algebraic graph algorithms, group theory, and database design. The class begins with a number of practical problems, offers an introduction to the appropriate theory, and then demonstrates how to apply the theory to the aforementioned problems. Students apply these ideas in a final project of their choosing. The course contains a number of smaller assignments which provide students with appropriate software infrastructure for completing their final projects.

Course Outcomes

Course Goals for Students

  • Gain an awareness of D4M: Dynamic Distributed Dimensional Data Model, a breakthrough in computer programming that combines the advantages of five distinct processing technologies to provide a database and computation system that addresses the problems associated with Big Data
  • Become facile with D4M, such that participants can begin applying it to their own problems
  • Understand the new mathematical concepts that have emerged as a result of bringing together signal processing and Big Data concepts

Instructor Insights

In the following pages, Jeremy Kepner describes various aspects of how he taught D4M: Signal Processing on Databases.

Curriculum Information


18.06 Linear Algebra and familiarity with MATLAB®

Requirements Satisfied



This course was offered at MIT Lincoln Laboratory once during Fall 2012.


Grade Breakdown

Homework assignments were optional and not graded.

Instructor Insights on Assessment

Jeremy Kepner shares his insights about Homework Assignments that Spotlight Application.

Student Information


50 students

Typical Student Background

Participants were all affiliated with MIT Lincoln Laboratory and held master’s and bachelor’s degrees in a wide range of fields.

Course Info

As Taught In
January IAP 2020
Learning Resource Types
Lecture Videos
Lecture Notes
Instructor Insights