Corporate AWS Training

Design available, cost-efficient, fault-tolerant, and scalable distributed systems on AWS.

Build complex solutions incorporating data services, governance, and specialized use cases on AWS.

Apply the AWS Well-Architected Framework to evaluate and improve your cloud workloads.

Understand the fundamentals of agentic AI systems and how to build them on AWS.

Build and deploy agentic AI applications using Amazon Bedrock AgentCore.

Design and implement advanced multi-agent architectures and orchestration patterns on AWS.

Explore the fundamentals of generative AI and how AWS services enable GenAI applications.

A business-focused overview of generative AI strategy, opportunities, and risks for leaders.

Build production-ready generative AI applications using Amazon Bedrock and related AWS services.

Advanced techniques for building, fine-tuning, and deploying generative AI models on AWS.

Apply data science techniques using Amazon SageMaker for real-world ML workflows.

Master Amazon SageMaker Studio for end-to-end machine learning development.

Implement MLOps practices to automate and streamline ML pipelines on AWS.

Build, train, and deploy machine learning models at scale using AWS services.

Foundational understanding of AWS Cloud concepts, services, security, and pricing.

Introduction to core AWS services, architecture, and hands-on technical fundamentals.

A concise overview of AWS Cloud value, strategy, and business transformation for leaders.

Design and build scalable data lakes on AWS using S3, Glue, Athena, and Lake Formation.

Implement batch data processing pipelines using AWS analytics services.

Build cloud data warehouse solutions using Amazon Redshift for analytics at scale.

Process real-time data streams using Amazon Kinesis and related AWS services.

Advanced data warehousing concepts and implementation using Amazon Redshift.

Build end-to-end data engineering pipelines using AWS data services.

Design and build modern applications using DynamoDB and other AWS NoSQL services.

Learn to develop secure, scalable cloud applications using the AWS SDK and core services.

Implement DevOps practices using AWS tools for CI/CD, automation, and monitoring.

Deploy, manage, and scale containerized applications using Amazon Elastic Kubernetes Service.

Understand the AWS migration methodology, tools, and best practices for moving to the cloud.

Plan and execute cloud migrations using AWS Migration Hub, DMS, and related services.

Design and implement networking architectures for cloud applications on AWS.

Manage and operate AWS infrastructure using Systems Manager, CloudWatch, and automation tools.

Build event-driven serverless applications using Lambda, API Gateway, and related services.

Understand AWS security fundamentals including IAM, encryption, and compliance.

Implement security controls and automate security operations across AWS workloads.

Select and implement the right AWS storage solutions for performance, cost, and durability.