Ideal for teams that…
Cloud, automation and CI/CD in practice — hands-on for engineering teams.
Basic knowledge of Python programming
Basic understanding of machine learning
Experience with cloud services (an advantage, but not mandatory)
What we actually do
- · Introduction to the AWS ecosystem and its AI/ML services
- · Configuring the AWS environment and managing access
- · Importing and processing data in AWS S3
- · Conducting EDA using AWS Glue and AWS Data Wrangler
- · Introduction to Amazon SageMaker
- · Automating model training with SageMaker Autopilot
- · Deploying and monitoring models via SageMaker Endpoint
- · Workshop: Training the first model – hands-on exercises with a real dataset
- · Model evaluation and results analysis
- · Overview of Amazon Bedrock and foundation models for generative AI
- · Customizing foundation models
- · Using RAG (Retrieval-Augmented Generation) to enhance GenAI intelligence
- · Integrating GenAI with external systems – GenAI agents in action
- · Applying guardrails as protective mechanisms for AI models
- · Hands-on exercises with Amazon Bedrock and Large Language Models (LLMs)
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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