MLOps training:
basic course

MLOps training:
basic course

Dive into the dynamic world of MLOps and master the art of bringing Machine Learning models to life with this MLOps training course

With our expert-led MLOPS training program,
designed to equip you with cutting-edge skills in modern application deployment and management.
Benefit from our wealth of experience from countless customer projects:

With this MLOps training, you will experience a balanced mix of theory, live demonstrations and practical exercises.

Learn the essential principles and concepts of MLOps, including integration into the DevOps and Machine Learning domains.

Dive into the use of specialized cloud platforms, data versioning and feature stores, the creation and management of ML pipelines.

get to know advanced MLOps tools and techniques, as well as methods for continuous integration and delivery (CI/CD).

MLOps Course – Upcoming Dates

06.02.2025

Basics in 8 hours

09.04.2025

Basics in 8 hours

In this MLOps course, you will learn the essential principles and concepts of MLOps, including integration into the DevOps and Machine Learning domains, the use of specialized cloud platforms, data versioning and feature stores, the creation and management of ML pipelines, as well as the deployment and monitoring of models. You will also get to know advanced MLOps tools and techniques, as well as methods for continuous integration and delivery (CI/CD).

Practical Applications That We Will Cover in the MLOps training:

  • 1
    Implementing and managing ML pipelines with Kubeflow and Apache Airflow.
  • 2
    Using TensorFlow, DVC, Feast, and dbt in practical exercises to create and deploy ML models.
  • 3
    Applying monitoring and metrics tools like Hydrosphere, Evidently.ai, and Grafana to track data and concept drift.
  • 4
    Hands-on activities for model deployment with FastAPI, Seldon Core, and TensorFlow Serving.
  • 5
    Executing CI/CD processes with tools such as Jenkins, Prefect, Airflow, Rundeck, Kedro, TFX, and Kubeflow.

After the MLOps training course, You Will Be Able To:

  • 1
    Understand and apply the importance of MLOps.
  • 2
    Effectively use machine learning concepts and environments.
  • 3
    Implement data versioning and feature stores.
  • 4
    Create and orchestrate ML pipelines.
  • 5
    Use machine learning frameworks such as Scikit-Learn, Keras, and TensorFlow.
  • 6
    Deploy and monitor models using advanced techniques and tools.
  • 7
    Integrate CI/CD tools and platforms into ML workflows.

This MLOps course is perfect for you if you…

  • You work or wish to work in the field of machine learning, data engineering, or DevOps.
  • You want to expand your knowledge in the deployment and management of ML models.
  • You want to gain practical experience with advanced MLOps tools and techniques.
  • You want to develop a deep understanding of the integration of machine learning into DevOps processes.

The MLOps training is NOT suitable for you if you …

  • You are not interested in the integration of DevOps and machine learning.
  • You do not have prior knowledge in the fields of machine learning, data engineering, DevOps, or general programming.
  • You are not willing to engage in practical exercises and projects.
  • You do not wish to acquire skills in using cloud platforms and advanced MLOps tools.

Agenda

Training

For small companies and teams that are new to the topic.

  • Introduction
  • Machine Learning Environments
  • Recap: Machine Learning Frameworks

  • Introduction to Versioning

  • DVC
  • Hands-on
  • Overview of Versioning Tools

  • Use Cases and Options

  • Deep-dive Feast
  • Hands-on

  • Data Pipelines Types and Characteristics

  • Frameworks for ML Pipelines
  • Hands-on

  • Saving and Loading Models
  • Serving Overview
  • Hands-on

Customized

For large companies and teams that want to master special challenges.

  • Transparancy and Explainability
  • Pillars of monitoring
  • Monitoring Frameworks
  • Hands-on

  • Your ecosystem
  •  Your best practises
  • further frameworks and hands-on according to your requirements

  • Introduction
  • Machine Learning Environments
  • Recap: Machine Learning Frameworks

  • Introduction to Versioning
  • Overview of Versioning Tools
  • DVC
  • Hands-on

  • Use Cases and Options
  • Deep-dive Feast
  • Deep-dive Hopswork
  • Hands-on

  • Data Pipelines Types and Characteristics
  • Frameworks for ML Pipelines
  • Focus: Airflow
  • Focus: Kubeflow
  • Hands-on

  • Saving and Loading Models
  • Serving Overview
  • Deployment Strategies
  • Hands-on

Hear from our satisfied training attendees

A1 Telekom Austria AG

Reinhard Burgmann
Head of Data Ecosystem

„UTA coached my team along the development process of the migration plan of our on premises data lake to the public cloud.

The outstanding level of expertise, both on a technical and organizational level, ensured a well-structured and realistic migration plan including timeline, milestones, and efforts.

The enablement of my team was at the center of a very smooth collaboration. Through UTA, we achieved our goal faster and reduced risks of the migration project significantly.

I highly recommend UTA’s services!“

Vattenfall

Bernard Benning
BA Heat

„I recently attended Vattenfall IT’s online Kafka training day hosted by Ultra Tendency, and it was an enriching experience.

The trainer, Ahmed, did a fantastic job explaining the theory behind Kafka, and the emphasis on practical application was great. The hands-on programming exercises were particularly helpful, and I’ve never experienced training with so many interactive examples!

Overall, I highly recommend this training to anyone who wants to improve their Kafka knowledge interactively and gain valuable skills.“

VP Bank

Eisele Peer
Lead Architect & Head of IT Integration & Development

“The MLOps training exceeded our expectations!

It offered a perfect blend of an overview, hands-on coding examples, and real-world use cases. The trainer answered all questions competently and adapted the content to fit our company’s infrastructure.

This training not only provided us with knowledge but also practical skills that we can apply immediately.“

Your investment

949 €plus VAT
  • Combination of theory and practice with live demos and exercises to actively develop skills.
  • Understand the application of DevOps principles in automating the machine learning lifecycle, from data preparation to model training.
  • Learn to effectively handle the complexities and challenges of managing machine learning models in a production environment.
Book now

Get to know your MLOps training professionals

Marvin Taschenberger

Professional Software Architect, Ultra Tendency

Hudhaifa Ahmed

Senior Lead Big Data Developer & Berlin Territory Manager, Ultra Tendency

Matthias Baumann

Chief Technology Officer & Principal Big Data Solutions Architect Lead, Ultra Tendency

Required hardware & infrastructure for your MLOps Training

  • You will need a PC or Mac with a web browser and MS Teams.
  • During the training, we will provide you with a virtual machine with the required local dependencies, services and root access.
  • This VM has a running Kubernetes cluster on which you can test and execute the training instructions.
  • You can access the machine via a browser or SSH if you wish and the network restrictions allow it.