Rust for Large Language Model Operations
Master LLMOps using Rust, integrating with HuggingFace and AWS, while building scalable AI solutions with focus on performance and safety.
Master LLMOps using Rust, integrating with HuggingFace and AWS, while building scalable AI solutions with focus on performance and safety.
This advanced course combines Rust programming with Large Language Model operations, teaching students to build efficient and scalable AI solutions. Learn to integrate Rust with leading frameworks like HuggingFace, Candle, and ONNX while leveraging GPU acceleration and cloud infrastructure. The curriculum covers essential topics from model training to deployment, including DevOps practices, security considerations, and performance optimization. Through hands-on projects building chatbots and text processors, students gain practical experience in production-ready LLMOps.
Instructors:
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What you'll learn
Apply Rust's safety and performance features in LLMOps infrastructure
Integrate Rust with HuggingFace and other LLM frameworks
Deploy and scale LLM solutions using AWS services
Implement CI/CD pipelines for LLM applications
Optimize model training and inference using GPU acceleration
Build production-ready AI applications with security best practices
Skills you'll gain
This course includes:
16 Hours PreRecorded video
6 quizzes, 5 ungraded labs, multiple external labs
Access on Mobile, Tablet, Desktop
Limited Access access
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There are 4 modules in this course
The course provides comprehensive training in using Rust for Large Language Model operations. Students learn to build and deploy scalable LLM solutions by combining Rust's performance capabilities with modern AI frameworks. The curriculum covers integration with HuggingFace Transformers, Candle, and ONNX runtime, along with cloud deployment on AWS. Special focus is given to performance optimization, security, and DevOps practices specific to LLMOps.
DevOps Concepts for MLOps
Module 1
Rust Hugging Face Candle
Module 2
Key LLMOps Technologies
Module 3
Key Generative AI Technologies
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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