Rust Data Engineering
This course is part of multiple programs. Learn more.
This comprehensive 4-week course teaches you how to leverage Rust for efficient and reliable data engineering workflows. You'll master Rust's data structures and collections for processing, explore safety and security features, and work with essential libraries like Diesel, Polars, and Apache Arrow. Through hands-on projects, you'll build data ingestion tools, ETL pipelines, and learn to interface with databases and cloud services. The course covers concurrent programming, performance optimization, and best practices for handling large datasets. By completion, you'll have practical experience in creating high-performance, secure data systems ready for real-world deployment.
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Instructors:
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What you'll learn
Leverage Rust's data structures and collections for efficient data manipulation
Implement secure and reliable data engineering solutions using Rust's safety features
Develop high-performance concurrent data processing applications
Create ETL pipelines and data ingestion tools using Rust
Integrate with databases REST APIs and cloud services
Optimize data processing performance using Rust's unique capabilities
Skills you'll gain
This course includes:
PreRecorded video
5 quizzes, 9 assignments, 13 ungraded labs
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 4 modules in this course
The course provides a thorough introduction to using Rust for data engineering applications. Starting with fundamental data structures and collections, it progresses through safety and concurrency features specific to data processing. Students learn to work with specialized libraries and tools while gaining practical experience with databases, APIs, and cloud services. The curriculum emphasizes hands-on learning through projects, covering everything from basic data manipulation to complex pipeline design. Special attention is given to performance optimization and security considerations in data engineering contexts.
Rust Data Structures: Collections
Module 1
Safety, Security and Concurrency with Rust
Module 2
Rust Data Engineering Libraries and Tools
Module 3
Designing Data Processing Systems in Rust
Module 4
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Rust Programming - Pragmatic AI, Data Engineering Foundations
Instructor
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.
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Frequently asked questions
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