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Deep learning in production

An AI model delivers lasting value only when its operation is controlled. With MLOps, connect deployment, monitoring and maintenance to organise the transition to production. Strengthen your ability to coordinate data and operations teams around models monitored over time.

Program PDF
3 days 21 hours
FC-DLP Code

Presentation

In recent years, deep learning has progressed rapidly. Frameworks and libraries have been developed and regularly updated. Nevertheless, there remains a lack of established solutions to manage, deploy and scale models. The maturity of deep learning research infrastructure also remains limited.

This level 2 deep learning course provides the skills needed to design effective deep learning models. You will also learn to adapt existing models and implement them. Finally, you will explore ways to address recurring deep learning challenges, such as a lack of labelled data and hyperparameter search.

By the end of this 3-day course, you will be able to create a deep learning model and adapt it using more advanced settings to improve performance. Labs throughout the programme will enable you to test your skills in deploying deep learning models to production.

Objectives

After completing the deep learning in production course, you will achieve the following learning objectives:

  • create deep learning models implemented with production-quality code;
  • use different approaches to deploy models to production;
  • make informed use of a specific deployment method.
Last update: 24/09/2026