PyTorch labs
Written and run on-device against real tensors.
Website undefined
Pay once. Fully unlocked. Verified by Apple.
This website download is a separate direct-distribution build from the Mac App Store edition. It contains no StoreKit purchase flow or subscription screen: every feature is available after the one-time website purchase.
Apple notarized this exact disk image after an automated malware check. It is signed with the publisher's Developer ID and its notarization ticket is stapled to the download, so Gatekeeper can verify it even when your Mac is offline.
How signing, notarization and installation work- Version
- 1.1 (build 205)
- Released
- undefined
- Requires
- macOS 14 or later
- Architecture
- Apple silicon and Intel
- Download
- 5.5 MB DMG
- Apple check
- Notarized · Developer ID signed
- SHA-256
4a6b82abd72c757ef26180a4cbfe1284e7538c23b4083f66df701226e614ad9e
What it is
What ML Engineering does
400 lessons from first Python through PyTorch, training, serving and MLOps, as a Mac app with runnable labs and an offline curriculum-grounded tutor.
Forty courses moving from Python fundamentals through PyTorch, training loops, evaluation, serving and MLOps. Labs execute locally so the gradient that does not descend is your gradient.
The tutor stays inside the curriculum, and the whole app works with no network.
How it does its job
Serving and MLOps
The part most courses skip: what happens after the notebook.
40 portfolio projects
Complete, runnable, yours.
What it doesn't do
Training large models needs hardware this app cannot conjure; it teaches the method, not the cluster.
Keep exploring
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Native, local-first, and yours
ML Engineering is a native Mac app distributed as a complete, fully activated download. No subscription, no account, no locked features, no tracking.
Buy & downloadGet ML Engineering
Choose $10 for one app, $20 for two different apps, or $49 for every published app through Stripe's hosted checkout. Download on the confirmation page or open the delivery email on your Mac. Each link is single-use; your email shows its exact expiry. Keep the installer for future use. If your link expires or the download fails, ask for a replacement link with your receipt; do not buy again.
Common questions
What is ML Engineering?
A full-featured native Mac learning app for becoming a production-capable machine learning engineer. 40 courses, 80 modules, and 400 interactive lessons run from first Python and statistics through PyTorch, computer vision, NLP, pipelines, serving, MLOps, and distributed training to a principal ML engineering capstone, with 140 editable code labs, 40 portfolio projects, and a private offline AI tutor.
Who is ML Engineering for?
ML Engineering is for Mac users looking for learn to code. 400 lessons from Python to PyTorch, serving and MLOps, with runnable labs and an offline tutor.
Which Macs can run ML Engineering?
ML Engineering requires macOS 14 or later. Supported architecture: Apple silicon and Intel. Check About This Mac before purchasing.
Is this the same ML Engineering edition as the Mac App Store version?
No. The Mac App Store edition can include Apple's in-app subscription system. The website Direct edition is a separately signed build with no StoreKit purchase flow: one website purchase unlocks the complete app with no recurring charge.
Is ML Engineering the full version, or are features locked?
The download is the complete app. There is no subscription, no locked tier, no account, and no trial timer — every feature is included.
How do I get ML Engineering?
Choose $10 for one app, $20 for two different apps, or $49 for every published app through Stripe's hosted checkout on this page. Download links are delivered on the confirmation page and by email. Each link is single-use; its exact expiry is shown in your delivery email. Keep the installer. If the link expires or a download fails, contact support@macossoftware.com with your receipt instead of buying again.
Is the ML Engineering Direct edition notarized by Apple?
Yes. Version 1.1 is signed with a Developer ID certificate, notarized by Apple, and distributed with a stapled notarization ticket. Its published SHA-256 checksum is 4a6b82abd72c757ef26180a4cbfe1284e7538c23b4083f66df701226e614ad9e.