Training: Amazon Bedrock – Practical Development of Generative AI Applications on AWS
Level
IntermediateDuration
24h / 3 daysDate
Individually arrangedPrice
Individually arrangedTraining: Amazon Bedrock – Practical Development of Generative AI Applications on AWS
The Amazon Bedrock training is a dynamic 2–3 day course focused on gaining the essential skills needed to design, integrate, and securely deploy generative AI solutions using Amazon Bedrock and AWS tools. The program is designed to provide maximum hands-on practice (80% workshops, 20% theory) and real-world use cases of Foundation Models (e.g., Anthropic, AI21, Meta) for business and automation purposes.
What will you learn?
- 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 modern AI-based recruitment tools can do
- Analyze CVs and candidate profiles
- Create job descriptions and postings
- Automate candidate communication and feedback
- Support recruiters in direct search and sourcing
- Build intelligent HR knowledge bases
- Predict job fit and employee retention risks
Who is this training for?
Developers and ML/AI engineers, cloud solution architects-
Solution architects and DevOps/Cloud specialists deploying AI in business
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Business and strategy teams building chatbots, generative systems, analytical APIs, or automation workflows
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IT managers and analysts looking to automate processes
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Professionals responsible for innovation and AI tool development within their organizations
Training Program
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Day 1: Introduction to Amazon Bedrock and Generative AI Fundamentals
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Module 1: Amazon Bedrock – Architecture and Capabilities
- 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
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Module 2: Getting Started – Environment Setup and API Calls
- 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
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Day 2: Building AI Solutions – Integration, Personalization, Automation
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Module 3: Extending Functionality and Integrating Bedrock Models
- 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
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Module 4: Security, Monitoring, and Best Practices
- 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
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Day 3: Advanced Deployment Scenarios and Final Projects
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Module 5: Case Studies and Extended Capabilities
- 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
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Module 6: Competence Development and Gaining Advantage with Generative AI
- Current trends and AWS AI development roadmap
- Best practices in documentation and AWS AI certification preparation
- Q&A: participants’ challenges, opportunities, and implementation plans
