For machine learning engineers

Your course ended at model.fit(). Your job didn't.

You can already train the model. Learn to deploy it and keep it running from the experts who wrote the book on it, from $10 a month.

Start Your Free TrialMeet the Experts

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Raschka
Cover image for Machine Learning with PyTorch and Scikit-Learn
McMahon
Cover image for Machine Learning Engineering with Python
Shah
Cover image for DevOps to MLOps Bootcamp: Build & Deploy ML Systems End-to-End
Raghunath
Cover image for Real-world End to End Machine Learning Ops on Google Cloud
Rothman
Cover image for Transformers for Natural Language Processing and Computer Vision

Sound familiar?

The model is the smallest box in the diagram

Most courses teach the box in the middle and stop there. In ExpertEdge, every box around it has a chapter of its own.

95% of the job is data cleaning, joining datasets together and feature engineering. 5% is fitting and testing models.

Answering what ML engineers do at work, Hacker News, June 2024

Your ML system in productionAfter Sculley et al., NIPS 2015

  1. ML code

    model.fit(X, y)

    Where your course stopped

  2. Configuration

    Reproducible and Reusable ML

    Cover image for Hands-On MLOps on Azure
    Chapter 3 · 2025Hands-On MLOps on Azure

  3. Data collection

    Building Good Training Datasets – Data Preprocessing

    Cover image for Machine Learning with PyTorch and Scikit-Learn
    Chapter 4 · 2022Machine Learning with PyTorch and Scikit-Learn

  4. Data verification

    Data Cleaning, Imbalanced Data, and Other Data Problems

    Cover image for XGBoost for Regression Predictive Modeling and Time Series Analysis
    Chapter 6 · 2024XGBoost for Regression Predictive Modeling and Time Series Analysis

  5. Feature extraction

    Utilizing Feature Store

    Cover image for Practical Machine Learning on Databricks
    Chapter 3 · 2023Practical Machine Learning on Databricks

  6. Machine resources

    Model Training Optimizations

    Cover image for Mastering PyTorch
    Chapter 12 · 2024Mastering PyTorch

  7. Process management

    From Model to Model Factory

    Cover image for Machine Learning Engineering with Python
    Chapter 3 · 2023Machine Learning Engineering with Python

  8. Serving infrastructure

    Moving a Model to Production

    Cover image for Modern Computer Vision with PyTorch
    Chapter 18 · 2024Modern Computer Vision with PyTorch

  9. Monitoring

    Monitoring and Autoscaling an ML Model

    Cover image for DevOps to MLOps Bootcamp: Build & Deploy ML Systems End-to-End
    Chapter 7 · 2025DevOps to MLOps Bootcamp: Build & Deploy ML Systems End-to-End
32courses on MLOps and model deployment

Who wrote it?

You may already have learned from one of them

Some of our experts teach machine learning at universities. Others lead the engineering teams that run it in production.

  • Cover image for Machine Learning with PyTorch and Scikit-Learn
    Sebastian Raschka, author of Machine Learning with PyTorch and Scikit-Learn

    Sebastian Raschka

    247k

    If you learned ML from a book, there's a good chance it was his.

    1 titleProfile
  • Cover image for Machine Learning Engineering with Python
    Andrew P. McMahon, author of Machine Learning Engineering with Python

    Andrew P. McMahon

    Data Scientist of the Year in 2019, on turning a notebook into a service.

    1 titleProfile
  • Cover image for DevOps to MLOps Bootcamp: Build & Deploy ML Systems End-to-End
    Gourav Shah, author of DevOps to MLOps Bootcamp: Build & Deploy ML Systems End-to-End

    Gourav Shah

    A DevOps consultant who takes one model from raw data to Kubernetes.

    6 titlesProfile
  • Cover image for Real-world End to End Machine Learning Ops on Google Cloud
    Siddharth Raghunath, author of Real-world End to End Machine Learning Ops on Google Cloud

    Siddharth Raghunath

    An engineering manager on running Kubeflow pipelines in Vertex AI.

    5 titlesProfile
Meet the Experts

Does it cover my cloud?

Deploy on the cloud your company already picked

Most MLOps courses teach the one platform their labs run on. ExpertEdge has a course for each, so you learn the one your team already runs.

Your model

churn-classifier

v3 · registered

Trained and tested. Nothing can call it yet.

Where do I start?

Software engineers get a list. So do you.

For coding interviews there's a list of 75 problems to work through. Set Machine Learning Engineer as your target and ExpertEdge lines up each skill and its courses, in order.

  1. What you've trained

    Where you are

  2. Computer Vision

  3. Deep Learning Architectures & Frameworks

  4. MLOps & Model Deployment

  5. Natural Language Processing

  6. Statistical Analysis & Predictive Modeling

  7. Supervised & Unsupervised Learning

  8. Machine Learning Engineer

    The goal

By design

What we left out on purpose

  • Mid-run, on demand

    Open the chapter when training stalls. No class to wait for.

  • Your own hardware

    You train on your own hardware. No GPU credits in the price.

  • Answers in the library

    Search the error, land on the course. Faster than a forum.

  • Past the basics

    We skip gradient descent. The courses start where lectures stop.

Bring your own model and your own GPUs. When it has to go live, the course is already in the library.

And the price?

One price, everything included

Monthly

Billed monthly

$15per month

Everything, month to month. Cancel anytime.

What's included

  • Every MLOps and deep learning course
  • The whole course library
  • Skills and a passport that stay yours
Start Free Trial

Annual

Billed yearly ($120)

$10per month

Everything for a third less, paid once a year.

What's included

  • Every MLOps and deep learning course
  • The whole course library
  • Skills and a passport that stay yours
Start Free Trial

No setup fees, no minimum seats. Invoicing available on plans of 20+ seats or more.

Comparing options? Read how ExpertEdge stacks up against Udemy Business, LinkedIn Learning, Coursera and edX in our comparisons

Our blog

Built by people who know how great teams run L&D programs that work at scale

Still not convinced ExpertEdge is the right fit for you? Review some of our thinking on enterprise learning, content strategy and more. See if we align via the full blog.

Content Strategy

The B2B learning content stack most enterprises miss

Enterprise L&D teams have approached content procurement the wrong way for a decade. What a mature B2B learning content stack looks like, and the layers most enterprises are missing.

Oli Huggins

Oli Huggins

CEO and Founder

Comparisons

ExpertEdge vs Coursera and edX for B2B learning

A side-by-side of Coursera, edX and ExpertEdge for enterprise learning content: what each does well, where each falls short, and how to choose.

Oli Huggins

Oli Huggins

CEO and Founder