Data Science W261

Machine Learning at Scale

3 units

Course Description

This course teaches the underlying principles required to develop scalable machine learning pipelines for structured and unstructured data at the petabyte scale. Students will gain hands-on experience in Apache Hadoop and Apache Spark.

Skill Sets

Code up machine learning algorithms on single machines and on clusters of machines / Amazon AWS / Working on problems with terabytes of data / Machine learning pipelines for petabyte-scale data / Algorithmic design / Parallel computing

Tools

Apache Hadoop / Apache Spark

Current Course Designers

Original Course Designer

Prerequisites

Data Science W205 & W207. Intermediate programming skills in an object-oriented language (e.g., Python). Master of Information and Data Science students only.

Courses

Video

datascience@berkeley | Machine Learning at Scale

datascience@berkeley | Machine Learning at Scale

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Course History

Fall 2020

Instructor(s): Ramakrishna Gummadi
Instructor(s): Ramakrishna Gummadi
Instructor(s): James York-Winegar, Jacob Baumbach
Instructor(s): James York-Winegar, Jacob Baumbach
Instructor(s): Kyle Hamilton

Summer 2020

Instructor(s): Kyle Hamilton
Instructor(s): Kyle Hamilton
Instructor(s): Kyle Hamilton
Instructor(s): Kyle Hamilton
Instructor(s): Ramakrishna Gummadi

Spring 2020

Instructor(s): Kyle Hamilton
Instructor(s): Kyle Hamilton
Instructor(s): Kyle Hamilton
Instructor(s): Kyle Hamilton
Instructor(s): Ramakrishna Gummadi

Last updated:

April 11, 2022