Software Architecture for Big Data Specialization

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Description

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.
The courses in Software Architecture 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. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

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 performanceThe 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.

What’s included