Data Science W205

Fundamentals of Data Engineering

3 units

Course Description

Data Science depends on data, and a core competency mandated by this reliance on data is knowing effective and efficient ways to manage, search and compute over that data. This course is focused on how data can be stored, managed and retrieved as needed for use in analysis or operations. The goal of this course is provide students with both theoretical knowledge and practical experience leading to mastery of data management, storage and retrieval with very large-scale data sets.

Course must be taken for a letter grade to fulfill degree requirements.

Skill Sets

Analytics Solution Architectures / Data at Scale Concerns and Tradeoffs / Distributed Data Processing / Relational Databases / Graph Databases / Streaming Data Applications / Cube Technology

Tools

Python / Relational databases / Hadoop / Map reduce / Spark / Cloud Computing (AWS)

Course Designers

Profile profile for mark.mims

Mark Mims

Lecturer

mark.mims@ischool.berkeley.edu

Information School Virtual Campus (Boulder)

Website

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Taylor Martin

Lecturer

taylormartin@ischool.berkeley.edu

Prior to Spring 2018, this course was titled “Storing and Retrieving Data”.

Prerequisites

Intermediate competency in Python, C, or Java, and competency in Linux, GitHub, and relevant Python libraries; or permission of instructor. Knowledge of database management including SQL is recommended but not required. MIDS students only.