Generative AI and LLMs on AWS
Master deploying and optimizing large language models on AWS through hands-on training in architecture, scaling, and compliance.
Master deploying and optimizing large language models on AWS through hands-on training in architecture, scaling, and compliance.
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
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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