Our Upcoming Training Programs

Course Description

Stepping beyond the foundational theory and applications of Machine Learning (ML), the “Effective MLOps” bootcamp delves into the crucial territory of operationalizing ML models for real-world deployment. From the meticulous process of requirement collection to the sophisticated art of model monitoring, this training covers the gamut of ML operations (MLOps) in a comprehensive manner.

Effective MLOps Bootcamp

Coming soon!

  • Opening in 2024

  • Online

  • English

  • Professional

Notify me when the next training is updated! 

Module 1 : Data, Model & Experiment Management

  • What is MLOps
  • MLOps maturity levels
  • Introduction and data understanding
  • Data cleaning and modeling
  • Data, code, experiment versioning

Key learnings

  • Learn ML & MLOps fundamentals
  • Build and compare an end-to-end ML models
  • Master Version Control System (DagsHub, GitHub)

Module 2 : Tooling, Infrastructure & Deployment

  • Backend and Frontend parts (Create restAPI using FastAPI & Create frontend using Streamlit framework)
  • Containerization (Docker)
  • Deploy the application to cloud provider (AWS, Heroku)
  • CI/CD/CT pipeline (Jenkins, GitHub Actions)

Key learnings

  • Master deploying ML system
  • Get hands-on experience in automatisation process for ML system

Module 3 : Serving, Testing and Validating the ML system

  • Testing: unit, integration
  • Testing data and models using Deepchecks
  • Monitoring ML-based services
  • Configure Arize AI as Machine Learning monitoring system

Key learnings

  • Get hands-on experience in testing and monitoring for ML system

What you will learn?

This training aims to teach practical aspects of productionizing ML services from collecting requirements to model deployment and monitoring.


Benefits: Master a set of tools and practices that helps you create a reliable Machine Learning model and make it to production

Your profile

  • Data scientists
  • ML engineers
  • software and data engineers interested in learning about putting ML in production.


This training program is designed for the participants who possess the following skills:

  • Python
  • Docker
  • Being Comfortable with command line
  • Knowledge on machine learning
  • Prior programming experience (at least 1+year)


Upon completion of this training program, you will be awarded a Certificate of Attendance, jointly issued by Machine Learning Architects Basel and our Digital Innovation Academy, recognizing your successful completion of the course.