Generative AI on AWS – Independent Course for IT Professionals
AI Training
Discover how to harness the power of AWS generative AI services, including AWS Bedrock, to build real-world AI applications. This hands-on, practical training teaches IT professionals how to develop intelligent solutions such as chatbots, document processing tools, and Retrieval-Augmented Generation (RAG) systems using foundation models and AWS infrastructure.
From £299 per person
Discounts for groups of 6+
Discounts for groups of 6+
From £299
Per person
Onsite
Live online
1 day
Target Audience:
IT professionals, developers, and technical leaders seeking practical skills to implement generative AI using AWS services like AWS Bedrock. Ideal for those with basic AWS knowledge aiming to build, deploy, and manage AI applications without prior AI experience.
Prerequisites:
Basic familiarity with AWS services and cloud computing concepts, experience with at least one programming language (Python preferred), and an active AWS account for hands-on labs. No prior AI or machine learning experience is required.
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7 lesson covers:
Introduction to Generative AI on AWS
Learn the fundamentals of generative AI and its applications in IT. Explore AWS’s generative AI service ecosystem, including AWS Bedrock, and discover practical use cases for enterprise AI adoption.
AWS Bedrock Fundamentals
Gain knowledge of AWS Bedrock as a fully managed service for foundation models. Compare leading models such as Anthropic Claude and Meta Llama, and understand model tuning, cost factors, and API usage.
Hands-on Lab: First Steps with AWS Bedrock
Set up AWS Bedrock access, practice prompt engineering, and develop simple text generation and conversational AI applications using AWS APIs.
AWS Generative AI Integration Patterns
Design scalable AI architectures using AWS Lambda, Amazon SageMaker, and SDKs. Learn security best practices and optimisation techniques for generative AI applications on AWS.
Hands-on Lab: Building Your First AWS GenAI Solution
Build a document analysis and Retrieval-Augmented Generation (RAG) system using AWS Bedrock, Amazon OpenSearch, and S3. Configure secure IAM roles and implement monitoring and troubleshooting.
Cost Management and Optimisation
Understand AWS pricing for generative AI, analyse cost drivers, and implement cost-saving architectural strategies. Set up budgets and alerts to manage AI workloads efficiently.
Implementation Planning and Next Steps
Develop a strategic 30-60-90 day roadmap for generative AI adoption on AWS. Address governance, compliance, success metrics, and ongoing learning resources. Includes an open Q&A to address practical implementation questions