LLMOps
Operationalizing large language models specifically — prompt versioning, evaluation, cost, and deployment at scale.
One-time course fee
Who should take this?
ML, platform, DevOps, SRE, and operations professionals responsible for production reliability.
Capability developed
Operate models and AI services reproducibly with evaluation, monitoring, deployment, and incident controls.
Professional application
MLOps, LLMOps, AIOps, platform enablement, or production-readiness engagements.
What’s inside this track
- 1Prompt & Model Lifecycle Management
Build: Version-control a real prompt library across environments.
Evidence: Prompts stop breaking silently when someone 'just edits' one.
- 2Evaluation at Scale
Build: An automated eval suite for a real LLM feature.
Evidence: Catches quality regressions before users do.
- 3Deployment & Infrastructure
Build: Deploy an LLM service with a CI/CD gate tied to eval results.
Evidence: Ships model and prompt changes without breaking production silently.
- 4Production Case Project
Build: Capstone: an agentic AI project (e.g. a trip planner) shipped with full LLMOps practices.
Evidence: Owns the entire operational lifecycle of an LLM feature, not just the demo.
What you get
What you will own
Not a promise — a concrete list of what you personally build and can show a buyer, pulled from this course’s real curriculum.
- A working project: Version-control a real prompt library across environments.
- A working project: An automated eval suite for a real LLM feature.
- A working project: Deploy an LLM service with a CI/CD gate tied to eval results.
- A working project: Capstone: an agentic AI project (e.g. a trip planner) shipped with full LLMOps practices.
- A completed capstone: Agentic Trip Planner with Full LLMOps Lifecycle, scored across multiple dimensions
- A portfolio entry documenting how you built it, not just that you finished
- Verified skill evidence — tied to real work, not a self-rating
What you’ll prove — and own — by the end
Completion isn’t the finish line. This is what turns the course into evidence you can actually use.
Personalised from day one
A short entry diagnostic flags which modules to move through quickly and which to slow down on — the full curriculum stays available either way.
Evidence, not checkmarks
Skills track through a real mastery ladder — module completed, exercise practiced, project shipped — not just “lesson viewed.”
Your Final real-world project, AI-defended
Agentic Trip Planner with Full LLMOps Lifecycle — submit real work, defend your decisions to an AI interviewer, get scored feedback across multiple dimensions.
A portfolio you can use today
Turn a finished project into a case study, resume bullets, and an interview story — drafted from your real work, yours to review before you use it anywhere.
Connect this course to practical work
See how Ropes links a skill to a business problem, portfolio proof, a bounded service, and responsible client delivery. No client or income outcome is guaranteed.
Earnings potential
A simple illustration of how freelancers commonly structure retainer pricing once they’re taking on client work.
Ops & observability retainer
Illustrative example — your results will vary based on niche, effort, and client base.
Industry snapshot
Real, sourced research — current tools, market signal, and named case studies, each with a citation. Not marketing copy.