36-615 Software for Large-Scale Data

6 units, Carnegie Mellon University

This course is for Master of Applied Data Science (MADS) students only. In this course, we'll begin working with two software systems designed to conduct statistical modeling of large and complex datasets. We will introduce PyTorch as a framework for deep learning, exploring different neural network architectures and computational techniques. We will return to Apache Spark, using its machine learning library to fit various ML models to distributed datasets. All examples and assignments will be written in Python. Students in this course should have prior experience programming in Python (such as through 36-650), using Git, and working from the command-line shell.

Prerequisites: none listed

Offered: Spring 2027, Spring 2026

Courseweave needs JavaScript to show sections, workloads and planning tools.