A self-paced course on getting models into production and keeping them working. It covers six stages: what separates an ML engineer from a data scientist, data and feature engineering, training and evaluation that survives contact with reality, deployment patterns, monitoring and retraining, and the platform and cost work that makes the whole thing sustainable.
The emphasis is on the engineering around the model rather than the model itself, because that is where most production ML fails. Tech Skills Library is independent and issues no certification or credential.
About this courseThis is a self-paced educational course. Completing it does not award a professional certification, license, degree or academic credit, and it does not count toward any licensing or continuing-education requirement. Exam-prep courses are independent study material: we are not affiliated with or endorsed by the exam provider, no exam voucher is included, and a certification is only awarded by the provider after you pass its exam. It makes no promise of employment, pay or exam results.