Generative AI and LLMs on AWS
This course is part of Large Language Model Operations (LLMOps).
This comprehensive course teaches professionals to deploy and manage generative AI models on AWS. Students learn to select optimal architectures, implement cost-effective scaling solutions, and ensure regulatory compliance. The curriculum covers essential skills including AWS Bedrock implementation, CI/CD pipeline development, monitoring systems, and differential privacy techniques. Through hands-on labs and real-world projects, participants gain practical experience in operationalizing LLMs using cloud-native services.
Instructors:
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What you'll learn
Deploy and scale large language models effectively on AWS
Optimize cost and performance using auto-scaling and spot instances
Implement monitoring systems and CI/CD pipelines for LLMs
Ensure regulatory compliance with differential privacy techniques
Master AWS tools including Bedrock and CodeWhisperer
Skills you'll gain
This course includes:
PreRecorded video
Labs, Projects, Hands-on Exercises
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 deploying and managing generative AI models on AWS. Students learn cloud-native services, architecture selection, performance optimization, and compliance implementation. The curriculum emphasizes hands-on experience with tools like Amazon Bedrock and AWS CodeWhisperer.
Getting Started with Developing on AWS for AI
Module 1
AI Pair Programming from CodeWhisperer to Prompt Engineering
Module 2
Amazon Bedrock
Module 3
Project Challenges
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: Large Language Model Operations (LLMOps)
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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