Big Data Systems

Catalog description

This graduate-level course offers a comprehensive exploration of the principles, architectures, and techniques essential for designing scalable, data-intensive systems. Students will delve into the intricacies of distributed systems, covering data storage, batch processing, stream processing, and data warehousing technologies. The course emphasizes building reliable, maintainable applications and covers cutting-edge tools and frameworks, such as Apache Spark and Kafka. By the end of the course, students will be equipped to architect data systems that efficiently manage data across various storage and processing frameworks, addressing real-world scalability and reliability challenges. Course Learning Outcomes 1. Gain the ability to critically analyze and evaluate different data-intensive systems. 2. Enhance their problem-solving skills by designing scalable, distributed data architectures and demonstrate strong communication abilities in presenting technical concepts and solutions. 3. Cultivate their research skills through independent projects that require synthesis and application of advanced concepts in data engineering and distributed systems. 4. Get prepared to tackle complex data challenges in both academic and professional settings. View Class Schedule