Free course for linguists on MT post-editing and QA, from a localization vendor

I work at Alconost, a localization vendor. We've just released a free course for translators, and since a good part of it is about post-editing I thought it belonged here.

It's the Foundation course. It covers things most translators learn on the job, one project at a time:

• how MQM categories and severity levels are assigned
• what a light post-editing brief expects from you compared to a full one
• and what to do when a reviewer flags something you're sure is right

More advanced courses for specific language pairs are on our roadmap.

The MTPE module starts from one idea: MT errors tend to repeat. If an engine mishandles a term or a construction in one segment, it will often do the same in similar segments across the project. Not always, since context changes the output. But it happens often enough that once you catch one such error, it's worth checking the rest of the project for the same pattern.

The module walks through seven MT error types. Here come three of them, with the examples the course uses (shown in English, source against what the engine produced):

Placeholder broken.
Source: "Welcome back, {username}!"
Engine output: "Welcome back, {user name}!"
The engine treated the placeholder as text and tidied it up. The sentence reads fine, review lets it pass. But the app is looking for {username} exactly, and {user name} with a space means nothing to it, so the user's name never shows up, or the string breaks.

Omission - a dropped negation.
Source: "Do not take with alcohol."
Engine output: "Take with alcohol."
Fluent, grammatical, and potentially harmful - the instruction is reversed. In medical, legal or safety content this is the first thing to check for.

Hallucination.
Source: "Harvest it!"
Engine output: "Save it!"
The output is fluent and nothing looks broken, so it passes a quick read.

The rest of the module covers:

• light versus full post-editing shown on the same string under two different briefs;
• post-editing distance and what it tells you when it stays high across a project;
• and how to decide, segment by segment, whether to accept the MT output, edit it, or reject it and translate from scratch.

The other modules cover MQM categories and severity on sample strings, LQA and how to rebut a review finding you disagree with, file formats and segment structure (source, target, context, placeholders), plus a short final assessment and an optional data annotation module.

The course doesn't cover automatic metrics. No COMET, BLEU or similar, because the course is designed for people doing the post-editing, not for people evaluating engines. It's engine-agnostic; the engine comparison in it is illustrative, not a benchmark, and is labelled that way.

The course takes about an hour in total. Everything is in English and language-neutral. You sign up with an email, and the certificate goes there.

academy.alconost.com

If you do post-editing work now, I'd love to know how much of the course content matches what you actually get asked to do, and what you would like covered in more depth.