Title: Generative AI and LLMs on AWS

Location: US

Company: Pragmatic AI Labs

About this course:
Master deploying generative AI models like GPT on AWS through hands-on labs. Learn architecture selection, cost optimization, monitoring, CI/CD pipelines, and compliance best practices. Gain skills in operationalizing LLMs using Amazon Bedrock, auto-scaling, spot instances, and differential privacy techniques. Ideal for ML engineers, data scientists, and technical leaders.
Course Highlights:

Choose optimal LLM architectures for your applications

Optimize cost, performance and scalability with auto-scaling and orchestration

Monitor LLM metrics and continuously improve model quality

Build secure CI/CD pipelines to train, deploy and update LLMs

Ensure regulatory compliance via differential privacy and controlled rollouts

Real-world, hands-on training for production-ready generative AI

Unlock the power of large language models on AWS. Master operationalization using cloud-native services through this comprehensive, practical training program.

Deploying large language models on AWS

Selecting optimal LLM architectures and models

Optimizing LLM cost, performance, and scalability

Monitoring and logging LLM metrics

Building reliable LLM CI/CD pipelines

Ensuring regulatory compliance for LLM deployment

Hands-on LLM operationalization using Amazon Bedrock

Unlock scalable generative AI with expert training on deploying and optimizing large language models on AWS for peak performance and compliance.

Duration: 4 weeks

Curriculum:
- Deploying large language models on AWS
- Selecting optimal LLM architectures and models
- Optimizing LLM cost, performance, and scalability
- Monitoring and logging LLM metrics
- Building reliable LLM CI/CD pipelines
- Ensuring regulatory compliance for LLM deployment

- Hands-on LLM operationalization using Amazon Bedrock