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Machine Learning in Production in Python

Elevate your machine learning skills to production level with this focused skill track. Designed for (aspiring) data scientists and machine learning engineers, this track offers a streamlined pathway to mastering the deployment and maintenance of machine learning models. Dive into the fundamentals of MLOps, including strategies for efficient model lifecycle management. Dive into MLflow to master interactively the deployment and tracking of machine learning models with one of the most popular MLOps tools, and apply the learned skills in a hands-on project. The track further enhances your ability to maintain and monitor deployed models, ensuring they continue to perform optimally amidst evolving data landscapes. You’ll also explore the practical benefits of versioning data using Data Version Control (DVC) to manage and version your machine learning projects effectively. By the end of this skill track, you'll be proficient in deploying, monitoring, and managing machine learning models, preparing you to successfully implement ML applications in any organization.

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Loved by learners at thousands of companies

1
Theory
MLOps Concepts

Discover how MLOps can take machine learning models from local notebooks to functioning models in production that generate real business value.

2 hours

Folkert Stijnman Headshot

Folkert Stijnman

ML Engineer

2
Python
Introduction to MLflow

Learn how to use MLflow to simplify the complexities of building machine learning applications. Explore MLflow tracking, projects, models, and model registry.

4 hours

Weston Bassler Headshot

Weston Bassler

Senior MLOps Engineer

3
Python
Predicting Temperature in London

Perform a machine learning experiment to find the best model that predicts the temperature in London!

2 hours

Folkert Stijnman Headshot

Folkert Stijnman

ML Engineer

4
Theory
Monitoring Machine Learning Concepts

Learn about the challenges of monitoring machine learning models in production, including data and concept drift, and methods to address model degradation.

2 hours

Hakim Elakhrass Headshot

Hakim Elakhrass

Co-founder and CEO of NannyML

5
Python
Monitoring Machine Learning in Python

This course covers everything you need to know to build a basic machine learning monitoring system in Python

3 hours

Hakim Elakhrass Headshot

Hakim Elakhrass

Co-founder and CEO of NannyML

6
Python
Introduction to Data Versioning with DVC

Explore Data Version Control for ML data management. Master setup, automate pipelines, and evaluate models seamlessly.

3 hours

Ravi Bhadauria Headshot

Ravi Bhadauria

Senior Machine Learning Engineer

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Instructors

  • Folkert Stijnman Headshot
    Folkert StijnmanML EngineerSee Folkert Stijnman's Portfolio
  • Weston Bassler Headshot
    Weston BasslerSenior MLOps EngineerSee Weston Bassler's Portfolio
  • Hakim Elakhrass Headshot
    Hakim ElakhrassCo-founder and CEO of NannyMLSee Hakim Elakhrass's Portfolio
  • Maciej Balawejder Headshot
    Maciej BalawejderData Scientist at NannyMLSee Maciej Balawejder's Portfolio

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