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MLOps

MLOps in Production

The operational discipline behind ML that survives contact with users

4.7· 385 student reviews
Level: AdvancedDuration: 6 monthsCredits: 24Tuition: $699 CADLead instructor: Marie-Claude Bouchard
Enroll now — $699 CADCompare programs

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.

4.7
385 reviews
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    286
  • 4★
    87
  • 3★
    8
  • 2★
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  • 1★
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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.

01Month 1 — MLOps Foundations02Month 2 — CI/CD for ML03Month 3 — Feature Stores and Registries04Month 4 — Serving and Scaling05Month 5 — Monitoring and Reliability06Month 6 — Capstone

Six-month 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

Role 1
MLOps Specialist
Role 2
Senior MLOps Practitioner
Role 3
MLOps Team Lead

Frequently asked questions

How much does the MLOps in Production cost?▾

Tuition is $699 CAD. You can pay in full at checkout or choose an interest-free monthly plan. A 30-day refund window applies from your start date.

How long is the MLOps in Production program?▾

6 months, cohort-based and fully online. Expect roughly 14 hours per week including live Thursday sessions at 7pm ET.

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 smart-ai-future.lovable.app/verify.

What is the refund policy?▾

Full refund within 30 days of your cohort start date, no questions asked. After day 30, prorated refunds are available per our Refund Policy.

Who teaches the program?▾

Working Canadian AI practitioners — not academics. Each cohort has a lead instructor plus a 1:1 mentor pairing for the duration of the program.