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Coursera

Rust DataOps: CI/CD and Containers for Data Pipelines

Pragmatic AI Labs via Coursera

Overview

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e.g. This is primarily aimed at first- and second-year undergraduates interested in engineering or science, along with high school students and professionals with an interest in programming.Master modern DataOps practices by building robust, automated CI/CD pipelines for data applications using Rust. This course teaches you how to design, implement, and maintain end-to-end deployment pipelines that combine the safety and performance of Rust with industry-standard DevOps tooling. You will start with the fundamentals of Continuous Integration and Continuous Deployment, then progress to advanced topics including matrix builds, interdependent jobs, Dockerfile linting, and container packaging. Hands-on labs use GitHub Actions, Makefiles, and Docker to give you practical experience automating the full software delivery lifecycle for data-driven Rust applications. By the end of the course, you will be able to: write production-grade GitHub Actions workflows; lint, test, and release containerized Rust applications; manage complex job dependencies and matrix configurations; and ship a complete end-to-end deployment pipeline. Whether you are a data engineer modernizing your pipelines or a Rust developer adopting DataOps, this course gives you the patterns and tools to deliver reliable, automated, container-based data systems.

Syllabus

  • Week 0: Welcome
    • Covers Alfredo Deza, what you build, and parallel AI track.
  • Week 1: DevOps Foundations and Containerization
    • Covers DevOps as culture, automation as default, shared metrics, CALMS framework, and lean flow.
  • Week 2: CI/CD Pipelines
    • Covers CI = continuous integration, CD = continuous delivery, value to learners, SageMaker Canvas, and where it fits.

Taught by

Noah Gift and Alfredo Deza

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