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Cloud

AWS AI/ML

The AWS AI/ML training is an intensive two-day course focused on the practical use of AWS services for building, training, and deploying machine learning models.

Duration
16h · 2 days
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Who it's for

Ideal for teams that…

1 Developers and data engineers who want to expand their skills in machine learning on AWS
2 Data scientists and data analysts seeking to train and deploy ML models in production environments
3 IT specialists who want to use AWS AI/ML to automate data processing and predictions
Outcomes after the program

Cloud, automation and CI/CD in practice — hands-on for engineering teams.

✓

How to configure the AWS environment and manage access to AI/ML services

✓

How to perform exploratory data analysis and train ML models with Amazon SageMaker and Autopilot

✓

How to deploy ML models on SageMaker Endpoint and monitor their performance

✓

How to integrate ML models with other AWS services such as Lambda, Rekognition, and Comprehend

Requirements

What you should know before we start

  • Basic knowledge of Python programming
  • Basic understanding of machine learning
  • Experience with cloud services (an advantage, but not mandatory)
Program

What we actually do

Day 1: Introduction to AWS AI/ML and Predictive AI

  • · 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

Day 2: Advanced Techniques and Practical Applications with Generative AI

  • · 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)
Every module is adapted to your stack and context. The above is a starting point — not a fixed agenda.
How we work

From brief to retro in 30 days.

01

Brief & diagnosis

A call with the team lead + a short survey for participants. We define goals, gap and context.

02

Program customization

We adapt modules, case studies and code examples to your stack. Approval in 5 days.

03

Workshop

Trainer-led sessions, hands-on, code review. Mentor available between sessions too.

04

Retro + report

Outcome report for the team and lead. 30 days of consulting included.

Inquiry

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.

✓Quote within 48h of the brief
✓First session within 30 days
✓Pilot before the full decision
✓VAT invoice, payment in instalments possible

How we handle your data

We process your business data (name, work e-mail, phone number, company, job title) in order to handle your corporate training inquiry and prepare an offer. The data controller is infoShare Academy Sp. z o.o., Al. Grunwaldzka 472B, 80-309 Gdańsk. Providing the data is voluntary but necessary to receive a response. You have the right to access, rectify, erase or restrict the processing of your data and to object to it. Full information is available in our data processing notice.

Optional marketing consents

The controller of your personal data is infoShare Academy sp. z o.o. The rules for processing personal data are set out in the Privacy Policy and the Data Processing Notice.

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