Ideal for teams that…
Hands-on AI and data analytics workshops — built around your team's real cases.
How to quickly and securely launch AI projects with Amazon Bedrock
How to choose and integrate the right foundation models for your needs
How to automate business tasks using AWS tools
How to manage access, optimize costs, and monitor AI usage in your company
How to prepare for the role of AI expert in a cloud environment
How to build prompt chaining, analyze model performance, test, and document deployments
What we actually do
- · Overview of the Bedrock ecosystem and comparison with other AI tools
- · Foundation models in Bedrock (Anthropic, AI21, Meta, Stability, Amazon Titan)
- · Security and compliance – how Amazon protects data and supports regulations
- · Business scenarios for Bedrock and choosing the right model for your application
- · Setting up an AWS account, accessing Bedrock (console, SDK, CLI)
- · Workshop: quick deployment and testing of selected foundation models
- · Basic API integration with Python and JavaScript applications
- · Managing tokens, limits, and billing
- · Working with multimodal models (text, image)
- · Bedrock for content generation and analysis (prompt engineering, fine-tuning, chaining)
- · Building applications with Bedrock and cloud workflows
- · Integration with S3, Lambda, REST API – automation examples
- · Workshop: building your own chatbot/content generator
- · Cost monitoring and optimization strategies
- · IAM access control and security for Bedrock models
- · Monitoring model usage with CloudWatch, Billing, and alerts
- · Diagnosing and resolving common errors
- · Privacy best practices and impact assessment for AI deployment
- · Cost optimization, scaling deployments, and user management
- · Bedrock use cases in companies – document automation, offer generation, data analysis
- · Integrating Bedrock with other AWS services (SageMaker, API Gateway, Step Functions)
- · Workshop: developing a custom project and presenting results
- · Current trends and AWS AI development roadmap
- · Best practices in documentation and AWS AI certification preparation
- · Q&A: participants’ challenges, opportunities, and implementation plans
From brief to retro in 30 days.
Brief & diagnosis
A call with the team lead + a short survey for participants. We define goals, gap and context.
Program customization
We adapt modules, case studies and code examples to your stack. Approval in 5 days.
Workshop
Trainer-led sessions, hands-on, code review. Mentor available between sessions too.
Retro + report
Outcome report for the team and lead. 30 days of consulting included.
Send a brief. We'll reply within 1 day.
After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.
Thank you!
We'll get back to you within 1 business day.
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