Cloud Computing for Data Science

Master the tools and techniques that power large-scale data processing and analytics. This course introduces the principles and frameworks of Big Data Processing with Hadoop and Spark, enabling learners to manage, process, and analyze massive datasets efficiently. You’ll start by understanding the Hadoop ecosystem, including HDFS and MapReduce, and how distributed storage and computation work together to handle data at scale. Then, you’ll explore Apache Spark, a powerful framework for fast, in-memory data processing and real-time analytics. Through guided exercises and case studies, you’ll learn how to build scalable data pipelines, optimize performance, and apply transformations for business insights. By the end of this course, you’ll be equipped to handle complex data workloads using industry-standard big data tools. Ideal for aspiring data engineers, analysts, and developers, this course bridges data management and cloud computing—preparing you to design, implement, and manage big data solutions that drive intelligent decision-making in modern organizations.

Master the essential concepts and hands-on skills needed to understand cloud computing from multiple perspectives. This comprehensive course takes you from cloud computing history and definitions through advanced database technologies, providing both theoretical foundations and practical implementation experience. You'll explore how cloud platforms have transformed modern technology, learning to evaluate IaaS, PaaS, and SaaS service models while gaining hands-on experience with virtualization using VirtualBox. The course progresses through cloud data infrastructure, where you'll differentiate between databases, data warehouses, and data lakes, and learn to apply de-normalized schemas like Star and Snowflake for optimal performance. By course completion, you'll confidently compare and select appropriate database technologies—MySQL, MongoDB, and Neo4j—understanding ACID versus BASE properties and horizontal versus vertical scaling strategies. What sets this course apart is its balanced approach: combining historical context, architectural understanding, and practical coding exercises using Python, GitHub, and Flask. Whether you're transitioning into cloud roles or expanding your technical expertise, this course equips you with the foundational knowledge and practical skills essential for modern cloud computing careers.