Coursera – Software Architecture for Big Data Specialization 2024-9

Software Architecture for Big Data Specialization. This specialization teaches you how to design and build large, distributed systems that process large amounts of data. In this course, the fundamental concepts of software engineering and the principles of designing large systems with big data are thoroughly explored. You will learn how to create independent, high-performance data microservices and develop a distributed system over time. In the second course, you will learn how to take a big data processing system to production and transform it from a prototype into high-quality, reliable software. You will learn how to measure the performance of distributed systems and learn how to identify performance problems and implement scalable solutions to improve system performance. The specialization concludes with a practical project in which you will use your learning to build a production-ready distributed system. The course instructors will guide you along the way and share their experiences in building big data systems with you.

What you will learn:

• Practice software engineering principles: test-driven development, code refactoring, continuous integration, and continuous delivery
• Architecting and building a big or distributed data system: using REST collaboration, event-driven collaboration, and batch processing
• Creating a high-performance and scalable distributed system: that can handle big data

Who is this course suitable for?

• This course is suitable for software engineers who want to learn about the principles of building and architecting large software systems with big data.

Course details

• Publisher: Coursera
• Instructor: Tyson Gern , Mike Barinek
• Number of courses: 3
• Training level: Advanced
• Number of lessons: 35
• Training duration: 3 hours and 38 minutes

Course chapters

Course prerequisites

• None

Pictures

Sample course video

Download link

Download file – 389 MB

File(s) password: www.downloadly.ir

File size

389 MB