Software Architecture Patterns for Big Data (Coursera)

Software Architecture Patterns for Big Data can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics.

Course 2 of 3 in the Software Architecture for Big Data Specialization.

What You Will Learn

- Compare, measure, and test big data models for production use.

- Write custom performance tests to measure the characteristics of a distributed system.

- Use queues to horizontally distribute large workloads.

Syllabus

WEEK 1

Predictive Models

In this module, you will learn how to write tests that allow you to iterate on predictive models.

WEEK 2

Performance of Distributed Systems

In this module, you will learn how to write performance tests to ensure your distributed system operates as expected in production.

WEEK 3

Horizontal Distribution of Large Workloads

In this module, you will learn how to use queues to horizontally distribute large workloads.

WEEK 4

Highly Available Distributed Systems

In this module, you will learn the advantages and disadvantages of high availability distributed systems.