Fundamentals of Software Architecture for Big Data

The Fundamentals of Software Architecture for Big Data course is designed for individuals interested in understanding the principles of software engineering in the context of developing large-scale software systems that harness big data. Throughout the course, participants will explore essential software engineering concepts required to construct and expand large, data-intensive, distributed systems. The curriculum begins with an exploration of software engineering best practices and the creation of loosely coupled, highly cohesive data microservices. As the course progresses, participants will witness the evolution of a distributed system over time, gaining insights into the architectural and operational aspects of big data systems.

Key topics covered in the course include:

• Practice software engineering fundamentals such as test-first development, refactoring, continuous integration, and continuous delivery.
• Architecting and creating big data or distributed systems using rest collaboration, event collaboration, and batch processing.
• Developing performant, scalable distributed systems capable of handling big data.

Additionally, the course can be taken for academic credit as part of CU Boulder’s MS in Data Science or MS in Computer Science degrees, which are offered on the Coursera platform. These fully accredited graduate degrees provide targeted courses, short 8-week sessions, and pay-as-you-go tuition. Admission is based on performance in three preliminary courses, not academic history, making the degrees ideal for recent graduates or working professionals.