Every course from every provider we track, with the same filters over all of them: level, length, price, certificate and who stands behind it.
27 courses for “MLOps: Continuous Integration for Machine Learning”
2 hours
6 lessons, 149 minutes in all, from YouTube.
13 hours
Automotive Testing & Validation
15 lessons, 803 minutes in all, from YouTube.
New courses, a couple of emails a month. One click unsubscribes.
4 hours
Automotive Engineering Fundamentals
32 lessons, 267 minutes in all, from YouTube.
13 hours
27 lessons, 794 minutes in all, from Mechanical Engineering E-Learning.
1 minutes
A 1-minute video from Ansys Learning.
2 minutes
A 2-minute video from The Learning Studio.
2 minutes
A 2-minute video from The Learning Studio.
3 minutes
A 3-minute video from The Learning Studio.
18 minutes
Continuous integration applied to machine learning, in under twenty minutes.
5 hours
Five hours on MLOps: getting a model out of a notebook and keeping it running.
45 minutes
Forty-five minutes of scikit-learn, from fitting a model to scoring it.
13 minutes
Thirteen minutes on how a model is judged, and why accuracy alone is rarely the answer.
13 minutes
What machine learning is, explained without the mathematics, in thirteen minutes.
57 minutes
The opening lecture of MIT's introductory deep learning course.
9 hours
Eight and a half hours on deep learning, from neural networks to the frameworks that train them.
10 hours
Ten hours of deep learning from Edureka, from the neural network up.
24 hours
Forty-four lessons covering the statistics behind machine learning, from sampling to hypothesis testing and interview questions.
1 lesson, about 2 hours
A single session on product management, about 2 hours, published on YouTube by Great Learning. Watched here on the course page.
1 lesson, 8 minutes
An eight-minute introduction to machine learning: how a model learns from data, the difference between supervised and unsupervised learning, and where each is used.
1 lesson, about 12 hours
Twelve hours for people starting from nothing: the vocabulary, the mathematics that cannot be skipped, machine learning and deep learning, and worked examples throughout.
