Stony Brook University 3 credits AMS
This course introduces the tools for the analysis of big data sets on server machines. It teaches how to store, preprocess, analyze and visualize data arriving at high volume and velocity. In the first part of the course, we will cover programming in Python, from its basic libraries to more advanced methods for big data analytics, and machine learning. Emphasis will be on the implementation in Python and practical hands-on examples. Next, we will learn essential Shell scripting and terminal window commands for computations on server machines. We will introduce database management systems and SQL querying. In the second part of the course, we will discuss code version control and collaboration solutions in GitHub and GitHub Actions, microservices, containers (Docker and Kubernetes), API gateways, and other tools necessary in a professional data science pipeline. 3 credits Grading Letter graded (A, A-, B+, etc.)
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