This specialization is for software engineers interested in the principles of building and architecting large software systems that use big data. Through three courses you will learn about how to build and architect performant distributed systems from industry experts at Initial Capacity.
This specialization can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees offered on the Coursera platform. These fully accredited graduate degrees offer targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary 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
Applied Learning Project
The first course will introduce you to software architecture and design concepts necessary to build and scale large, data intensive, distributed systems. Starting with software engineering best practices and loosely coupled, highly cohesive data microservices, the course will take you through the evolution of a distributed system over time.
In the second course you will then learn what is needed to take big data to production, transforming big data prototypes into high quality tested production software. You will measure the performance characteristics of distributed systems, identify trouble areas, and implement scalable solutions to improve performance
The specialization concludes with a projects course in which you will use learnings from the first and second courses to build a production-ready distributed system. As you progress, your instructors will guide you around common pitfalls and share their experiences in building big data systems.
