Rust for Large Language Model Operations
This course is part of Rust Programming - Pragmatic AI.
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:
English
English
Powered by
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
Shareable certificate
Closed caption
Get a Completion Certificate
Share your certificate with prospective employers and your professional network on LinkedIn.
Created by
Provided by
Top companies offer this course to their employees
Top companies provide this course to enhance their employees' skills, ensuring they excel in handling complex projects and drive organizational success.
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
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
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.
Testimonials
Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.
Frequently asked questions
Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.