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Summer 2026
DS5110: Big Data Systems
Scalable data systems, parallel analytics, cloud infrastructure, and modern AI systems/infrastructure
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Overview
Systems for modern data science and AI
Welcome to the course of Big Data Systems. Scalable big data systems are a central part of modern data science. This course will cover topics including design and use of parallel dataflow systems (MapReduce/Hadoop and Spark), scalable and parallel Python analytics frameworks, machine learning systems (Ray), and cloud data systems (cloud storage, large ML infrastructure). A major component of this course is hands-on programming using scalable analytics tools and cloud resources on Amazon Web Services (AWS) or Google Cloud.
A major component is hands-on programming using scalable analytics tools and cloud resources on AWS or Google Cloud.
Course Topics
- Computer systems foundations and distributed computing
- Google File System, HDFS, and MapReduce
- Apache Spark and parallel dataflow systems
- Parallel Python analytics and Ray
- Cloud computing, storage, and serverless systems
- Large-scale AI and LLM systems
Syllabus
Course policies and expectations
Calendar
May 18 to June 12, Monday through Friday
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Lecture Materials
Slides, readings, and demos
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Coursework and deadlines
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