Rust Data Engineering
Develop advanced data engineering systems in Rust through practical projects in data processing, ETL workflows, and concurrent programming.
Develop advanced data engineering systems in Rust through practical projects in data processing, ETL workflows, and concurrent programming.
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
Instructor
30 Courses
Pioneering Tech Leader & AI Educator Shaping the Future of Machine Learning
Noah Gift is a distinguished technology leader and founder of Pragmatic AI Labs with a remarkable 30-year career spanning film, TV, telecom, social networks, startups, and big data, currently serving as an Executive-in-Residence at Duke University. As an AWS ML Hero and Python Software Foundation Fellow, he has authored best-selling books through O'Reilly and Pearson on DevOps, MLOps, data engineering, and cloud computing that are widely adopted by major universities. His expertise in MLOps, data engineering, cloud architecture, and Rust programming has led him to teach thousands of students across prestigious institutions including Duke, Northwestern, UC Berkeley, University of San Francisco, and UC Davis, while also collaborating with Caltech and JPL on automated IT systems. Gift's impact extends beyond academia through his work as a startup CTO, his role in developing scalable distributed systems, and his contributions as a keynote speaker at conferences focused on cloud development and ethical AI use, holding certifications from AWS, Google, and Microsoft, and having published over 100 technical works while conducting workshops for organizations like NASA, PayPal, and PyCon.
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