Coursera – Cloud Computing for Data Science Specialization

Build Scalable Cloud Solutions for Data Science.

What you’ll learn
✓ Design and deploy scalable cloud architectures for data-driven applications.
✓ Build and integrate RESTful web services within distributed systems.
✓ Implement big data workflows using Hadoop and Spark frameworks.
✓ Apply containerization and virtualization for efficient cloud deployment.

Skills you’ll gain
• Cloud Computing
• Cloud Computing Architecture
• Cloud Infrastructure
• Cloud Platforms
• Cloud Services
• Containerization
• Data Architecture
• Data Pipelines
• Data Processing
• Distributed Computing
• Google Cloud Platform
• Virtualization
• Web Services
• Show all

Tools you’ll learn
• Apache Hadoop
• Apache Spark
• Cloud Applications
• Cloud Storage
• Docker (Software)
• PySpark
• Restful API

This specialization equips learners with the essential skills to design, implement, and manage scalable data solutions using modern cloud technologies. Through three comprehensive courses, you’ll progress from foundational cloud computing concepts to advanced distributed systems and big data processing frameworks.

You’ll begin by understanding cloud architecture, service models, and data infrastructure in Cloud Computing Fundamentals. Next, in Distributed Systems and Web Services, you’ll gain hands-on experience designing RESTful APIs, deploying containerized applications, and integrating virtualization technologies. Finally, in Big Data Processing with Hadoop and Spark, you’ll learn to manage large-scale data processing pipelines and real-time analytics using industry-standard tools.

Designed for IT professionals, developers, and data practitioners, this course cluster bridges cloud engineering and data science, helping you build robust, data-driven applications that scale efficiently in the cloud.

Applied Learning Project
Learners will apply cloud and data processing skills through hands-on projects that simulate real-world scenarios. You’ll design and deploy RESTful APIs using Flask, implement containerized services with Docker, and build scalable data workflows using Hadoop and Spark. By completing these projects, you’ll gain the knowledge and skills to design, integrate, and manage distributed systems that support data-intensive applications in the cloud.

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