Rust for DevOps
Master DevOps principles using Rust programming for building, deploying, and monitoring applications with containerization, logging, and automation workflows.
Master DevOps principles using Rust programming for building, deploying, and monitoring applications with containerization, logging, and automation workflows.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Rust Programming Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
Instructors:
Alfredo Deza
English
ଓଡ଼ିଆ
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What you'll learn
Implement DevOps workflows using Rust and containers
Instrument applications with logging and monitoring
Automate system administration tasks efficiently
Build and manage CI/CD pipelines
Develop robust large-scale applications
Skills you'll gain
This course includes:
6.2 Hours PreRecorded video
4 quizzes, 1 assignment
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive course teaches DevOps principles and practices using Rust programming language. Students learn to implement containerization, monitoring, and automation for large-scale applications. The curriculum covers essential DevOps tools and workflows including ELK stack, Prometheus, GitHub Actions, and Jenkins. Topics include logging strategies, system administration automation, and CI/CD pipeline implementation.
DevOps Fundamentals
Module 1 · 7 Hours to complete
Implementing logging and monitoring strategies
Module 2 · 3 Hours to complete
Automating System management
Module 3 · 5 Hours to complete
CI/CD Platforms
Module 4 · 2 Hours to complete
Fee Structure
Instructors
Executive in Residence and Founder of Pragmatic AI Labs at Duke University
Noah Gift is the founder of Pragmatic AI Labs and serves as an Executive in Residence at Duke University, where he lectures in the Master of Interdisciplinary Data Science (MIDS) program. He specializes in designing and teaching graduate-level courses on machine learning, MLOps, artificial intelligence, and data science, while also consulting on machine learning and cloud architecture for students and faculty. A recognized expert in the field, Gift is a Python Software Foundation Fellow and an AWS Machine Learning Hero, holding multiple AWS certifications, including AWS Certified Solutions Architect and AWS Certified Machine Learning Specialist. He has authored several influential books, such as Practical MLOps, Python for DevOps, and Pragmatic AI, and has published over 100 technical articles across various platforms, including Forbes and O'Reilly. His extensive industry experience includes roles as CTO and Chief Data Scientist for notable companies like Disney Feature Animation, Sony Imageworks, and AT&T, contributing to major films like Avatar and Spider-Man 3. Gift's work has generated millions in revenue through product development on a global scale. He actively consults startups on machine learning and cloud architecture while leading initiatives to enhance data science education.
Alfredo Deza
1,11,315 Students
29 Courses
Adjunct Assistant Professor in the Pratt School of Engineering at Duke University
Alfredo Deza is an Adjunct Assistant Professor at Duke University's Pratt School of Engineering, where he specializes in teaching courses related to machine learning, data engineering, and programming. He has a rich background in software engineering and DevOps, with nearly two decades of experience working with various organizations, including ABC, Caltech, and Disney. Alfredo is also a co-author of several influential books on Python and MLOps, including Python for DevOps and Practical MLOps.On Coursera, Alfredo offers a wide range of courses such as "Advanced Data Engineering," "Introduction to Generative AI," and "MLOps Platforms: Amazon SageMaker and Azure ML." His courses are designed to equip students with essential skills in data engineering and machine learning operations, preparing them for careers in these rapidly evolving fields. Through his teaching and extensive industry experience, Alfredo aims to bridge the gap between theoretical knowledge and practical application in technology.
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