Preloader spinner

Our Operationalize Machine Learning and Generative AI Solutions AI-300 Course is a 4-day, instructor-led training course for data scientists, machine learning engineers and DevOps professionals who want to operate production AI systems on Microsoft Azure.

This AI-300 course covers MLOps and GenAIOps, Azure Machine Learning, Microsoft Foundry, GitHub Actions, infrastructure as code, automated deployment, model and agent evaluation, monitoring, tracing and optimisation of production machine learning and generative AI solutions.

Laptop displaying the text Microsoft Cloud & AI Platforms

Course Schedule

12
Oct 2026
Duration:

4 days

An icon of a clock

8:00am - 4:00pm

An icon representing a location

Online Live

Price:
Discounted Price:

£1,527 per delegate

9
Nov 2026
Duration:

4 days

An icon of a clock

9:00am - 5:00pm

An icon representing a location

Online Live

Price:
Discounted Price:

£1,527 per delegate

9
Mar 2027
Duration:

4 days

An icon of a clock

8:00am - 4:00pm

An icon representing a location

Online Live

Price:
Discounted Price:

£1,527 per delegate

Course Code: AI-300

Duration: 4 days

Course Overview

This course focuses on operationalising machine learning and generative AI solutions on Microsoft Azure. It covers the secure, scalable infrastructure and automated processes required to deploy, monitor, evaluate and improve production AI systems.

Target Audience

This course is intended for data scientists, machine learning engineers and DevOps professionals who want to implement production-grade MLOps and GenAIOps workflows using Azure-native services.

Course Objectives

  • Design and operate secure, scalable AI infrastructure.
  • Manage the machine learning model lifecycle with Azure Machine Learning.
  • Automate AI deployment using GitHub Actions and infrastructure as code.
  • Deploy, evaluate and monitor generative AI applications and agents.
  • Use tracing and observability to troubleshoot production AI systems.

Course Content

Operationalise Machine Learning Models

  • Experiments, hyperparameter tuning and pipelines in Azure Machine Learning.
  • GitHub Actions, feature-based development, environments and model deployment.

Operationalise Generative AI Applications

  • Plan and prepare a GenAIOps solution.
  • Manage prompts and agents with Microsoft Foundry and GitHub.
  • Evaluate, optimise, monitor, trace and debug AI applications.

Course Prerequisites

A basic understanding of machine learning, Python and DevOps practices is recommended, together with familiarity with Azure Machine Learning, source control, CI/CD and command-line tools.

Note - This course is delivered via our training partner Skillsoft Global Knowledge.

Global Knowledge logo

Public Schedule

RRP:  
£2,545 per delegate
Our price:  
£1,527 per delegate

Private Virtual Training (Teams / Zoom)

N/A

Private Onsite Training (at your offices)

N/A

Note

All prices exclude VAT at 20%.

VAT registration number: 450 4347 14

ENQUIRE or request a booking

You may also like...

Operationalize Machine Learning and Generative AI Solutions (AI-300)

Operationalise production AI on Azure using MLOps, GenAIOps, Azure Machine Learning, Microsoft Foundry, GitHub Actions, deployment and monitoring.

An icon of a clock
Duration:

4 days

Develop AI Cloud Solutions on Azure (AI-200)

Build and operate cloud-native AI solutions on Azure using containers, vector-enabled data services, event-driven integration, security and monitoring.

An icon of a clock
Duration:

5 days

Prepare and Visualize Data with Microsoft Power BI (DP-605)

Prepare, model and visualise data with Power BI, create interactive reports, use Copilot and manage workspaces and semantic models.

An icon of a clock
Duration:

1 day

Enquire or request a booking

Operationalize Machine Learning and Generative AI Solutions (AI-300)

If you would like to book a scheduled course, please let us know the number of delegates and your preferred date(s).
We will confirm availability and send you a booking form to complete.

Thank you!

Your enquiry has been received and we will come back to you shortly.

If you don’t hear from us within 2 working days, please check your junk or spam folder, just in case our response has ended up there.
Oops! Something went wrong while submitting the form.

Join our mailing list

Receive details on our new courses and special offers

Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.