MLOps in Production
The operational discipline behind ML that survives contact with users
About this program
A six-month program for engineers who own ML systems in production. Deep treatment of CI/CD for ML, feature stores, model registries, monitoring, drift detection, rollback strategies, on-call practices, and cost optimization. Includes a Canadian fintech case study on operating ML systems under OSFI guidance.
Student ratings
Excellent — 385 verified Canadian graduates rated this program 4.7/5. Reviews emphasize the applied capstone, instructor responsiveness, and career outcomes.
- 5★286
- 4★87
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- 2★2
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Who this program is for
- →Practitioners already shipping mlops work who want depth
- →Senior engineers, data scientists, and technical leads
- →Canadian residents seeking a verifiable diploma credential
Topics you'll cover
6 modules across 6 months — 24 lessons in total.
Full syllabus
Module 1 · Month 1 — MLOps Foundations▾
- L1Maturity models
- L2Stakeholders and ownership
- L3Tool landscape
- L4Reference architectures
Module 2 · Month 2 — CI/CD for ML▾
- L1GitHub Actions for ML
- L2Reproducible training jobs
- L3Testing data pipelines
- L4Model release management
Module 3 · Month 3 — Feature Stores and Registries▾
- L1Feast deep dive
- L2MLflow registries
- L3Lineage tracking
- L4Audit and compliance
Module 4 · Month 4 — Serving and Scaling▾
- L1Kubernetes for ML
- L2KServe and Seldon
- L3Autoscaling and batching
- L4GPU pools and spot economics
Module 5 · Month 5 — Monitoring and Reliability▾
- L1SLOs for ML
- L2Drift and quality monitoring
- L3Incident response
- L4Postmortems
Module 6 · Month 6 — Capstone▾
- L1Audit an existing system
- L2Propose and build improvements
- L3Run a real load test
- L4Present to faculty panel
What you'll be able to do
- ●Stand up a complete MLOps stack
- ●Implement progressive rollouts and automated rollback
- ●Build observability for ML systems
- ●Run cost-effective inference at scale
- ●Run a production ML on-call rotation
Career paths after graduation
Frequently asked questions
How much does the MLOps in Production cost?▾
Tuition is $175 CAD, paid once. You can pay in full at checkout or choose an interest-free monthly plan. A 30-day refund window applies from your enrollment date.
How long is the MLOps in Production program?▾
Self-paced. Most students complete it in 6 months at roughly 10 hours per week, but you can go faster or slower — you keep lifetime access.
What are the prerequisites?▾
Software engineering experience; Cloud fundamentals (AWS or GCP)
Is the diploma recognized in Canada?▾
Yes. Graduates receive the Altaris AI Academy Diploma in MLOps — a verifiable credential with a unique certificate number you can publish on LinkedIn and that any employer can verify at altarisai.org/verify.
What is the refund policy?▾
Full refund within 30 days of enrollment, no questions asked. After day 30, prorated refunds are available per our Refund Policy.
Who teaches the program?▾
Working Canadian AI practitioners — not academics. Every module is built and reviewed by a lead instructor working in the field today.