Software Architecture Patterns for Big Data

This course is designed for those who want to understand the architectural patterns needed to bring large software systems that use big data to production. You will turn big data prototypes into high-quality, tested software for production. By measuring the performance characteristics of distributed systems, you will identify bottlenecks and implement scalable solutions to improve performance. Upon completion of the course, you will know how to scale production data warehouses to handle load, design load tests to ensure applications meet performance requirements, and implement scalable solutions to improve performance. This course can be taken for academic credit toward CU Boulder’s MS in Data Science or MS in Computer Science programs, offered on Coursera. These fully accredited degrees offer focused courses, short 8-week sessions, and paid tuition. Admission to the program is based on three prerequisite courses, not academic history. CU degrees on Coursera are ideal for recent graduates or working professionals. Learn more: MS in Data Science: https://www.coursera.org/degrees/master-of-science-data-science-boulder MS in Computer Science: https://coursera.org/degrees/ms-computer-science-boulder