Bootcamp - Deploy your Machine Learning models

Master MLOps and generative AI from start to finish

Would you like to go beyond model training and learn how to deploy, monitor and optimise them in production? This intensive bootcamp immerses you in the heart of MLOps and modern AI applications, with a structured course based on concrete, professional projects.

 

You will learn how to manage the entire lifecycle of a machine learning model, from initial training to production monitoring. You will be introduced to best practices in monitoring, pipeline automation and deployment via API.
You will also explore the world of LLMs and RAG systems, learning how to evaluate their performance and structure reproducible pipelines. Finally, you will consolidate your knowledge by building a recommendation engine applied to precision agriculture, integrating MLOps pipelines and modern tools such as MLflow and CI/CD.

What you will learn:

• Managing the lifecycle of an ML model, from training to production monitoring;

• Deploying and monitoring a model via API and in the cloud;

• Evaluating RAG and LLM systems, with best practices for validation and testing;

• Designing a multi-source recommendation engine, applied to a concrete business case;

• Using essential tools such as MLflow and CI/CD to automate and improve the reliability of your workflows.

Our alumni share their stories

                                                                                       

"My mentor is flexible; he has adapted to my personal and family situation, which I really appreciate. At the same time, he is demanding and motivates me in a supportive way. It's a perfect balance."

 

                                                               

"We're not alone. We have support from our mentor, other students, and the OpenClassrooms team, who are always there to answer our questions. My apprehensions quickly disappeared!"

Who Is Eligible to Enroll?

To get started on this training, you need to have the following prerequisites:

• A good level of English for non-native speakers : you will need to provide a certificate not older than 2 years to demonstrate a minimum level of English B2.
  ◦ Certificates accepted:
  • • English Diploma from a secondary institution (private or public) or an accredited higher learning institution
      ▪ Linguaskill minimum score: 160
      ▪ BULATS minimum score: 60
      ▪ TOEIC minimum score: 785
      ▪ IELTS minimum score: 6.5
      ▪ TOEFL iBT minimum score: 88
• Access to a computer (PC or Mac), headphones, a microphone, a webcam, and a good internet connection for mentoring sessions (3.2 Mbps upload and 1.8 Mbps for download). You can use an internet speed test to find out, like High Speed Internet.
• At least 16 GB of RAM and 100 GB of free storage space available on your computer.
• Administrator rights to your computer in order to install required programs.
  
  
• Bachelor's degree in Data Science, Data Analytics, Computer Science, Statistics, Mathematics, Engineering, or related field
  
  OR
  
  
• One or more of the following professional certifications or equivalent/higher-level certifications:
  • Microsoft Azure AI Fundamentals (AI-900)
  • Microsoft Azure Data Fundamentals (DP-900)
  • Microsoft Certified: Azure Data Scientist Associate (DP-100)
  • AWS Certified Cloud Practitioner
  • Google Cloud Digital Leader
  
  OR
  
  
• Completion of all three of the following courses: • Learn Python Basics for Data Analysis • Perform an Initial Data Analysis • Use Python Libraries for Data Science