Three Programmes, Three Different Situations
A study group for people starting out with the material, an operations course for practitioners bridging the deployment gap, and a twelve-month partnership for institutions building internal teaching capacity.
← Back to HomeHow We Structure Programmes
Every Vectra Grove programme is built around the same basic assumptions: that people learn technical material by doing it, that peer exchange matters, and that a facilitator who has applied the content can answer questions that a course recording cannot.
Syllabi are published in full before enrolment. Assessments require a concrete output — a reproduction report, a deployed service, a documented teaching process. Completion alone is not sufficient to satisfy any of our assessments.
The three programmes are not a hierarchy. They serve different situations. The study group is for individuals working through foundational AI engineering material in a structured peer setting. The MLOps course covers an operational domain that comes after training — a separate and distinct body of knowledge. The institutional partnership is a different type of engagement entirely, aimed at transferring teaching capability rather than training individual participants.
AI Engineering Study Group
Eight weeks · Twice weekly · Online · Max 10 participants · RM 640
A rolling eight-week study group meeting twice weekly online, working through a published open curriculum with a facilitator who has taught the material before. No lectures are delivered; the facilitator sets the pace, asks questions, and reviews submitted work.
- Reading papers properly and reproducing small results
- Keeping a laboratory log during the programme
- Presenting findings to peers in group sessions
- Assessment: peer review plus written reproduction report
Prerequisites
Comfortable with Python and undergraduate mathematics (linear algebra, probability). No degree required.
How It Works
Facilitator selects reading from the published open curriculum. Material is circulated before each session.
Two group sessions per week. Facilitator asks questions; participants are expected to have done the reading.
Participants select a result from the reading list to reproduce. Lab logs are maintained throughout.
Written reproduction report submitted. Peer review conducted within the cohort.
Production Machine Learning Operations
Eleven weeks · 5 contact hrs + 9 lab hrs weekly · Online · RM 2,700
What happens to a model after training. Covers versioning of data and models, reproducible pipelines, containerisation, continuous integration for machine learning, feature stores, serving architectures, latency profiling, monitoring for drift and degradation, rollback strategy, cost accounting, and incident review.
- Deployment practice drawn from published industry frameworks (sources named)
- CI/CD pipelines for ML and containerisation
- Drift monitoring, rollback, and cost accounting
- Assessment: deployed service with monitoring + written operational review
Prerequisites
Familiarity with model training (any framework). Some exposure to software engineering practice. Comfort with command-line tooling.
Weekly Structure
Contact Hours (5/week)
Facilitated sessions covering the week's topic from the curriculum. Discussion of published frameworks and their practical application.
Lab Hours (9/week)
Scheduled laboratory time working toward the deployed service. Lab output forms part of the final assessment submission.
Assessment (Week 11)
Deployed service with monitoring in place, plus a written operational review defended in a session with the facilitator.
Institutional Curriculum Partnership
Twelve months · University / Polytechnic / Corporate academy · RM 4,650
A twelve-month partnership for university departments, polytechnics, or corporate academies that want to teach this material themselves. Includes a curriculum audit, a licensed syllabus and laboratory set, three instructor training weeks, a marking rubric and moderation process, sandbox compute for one cohort, and quarterly curriculum review calls.
- Curriculum audit and licensed syllabus + lab set
- Three instructor training weeks (on-site delivery)
- Marking rubric, moderation process, sandbox compute
- Quarterly review calls and annual cohort performance report
Important Note
The partnership transfers teaching capability. It confers no accreditation. Formal recognition of the partner institution's programmes remains the partner's responsibility.
Partnership Timeline
Curriculum audit. Review of the institution's existing AI-related teaching. Licence agreement signed.
Three instructor training weeks delivered. Marking rubric and moderation process handed over.
Partner institution runs first cohort with sandbox compute. Moderation support available. Review call.
Second review call. Annual cohort performance report prepared and submitted to the institution.
Which Programme Fits Your Situation?
Use this to self-select. If you are unsure, send an enquiry and we will tell you directly.
| Feature | Study Group | MLOps Course | Inst. Partnership |
|---|---|---|---|
| Who it is for | Individuals starting with AI engineering | Practitioners with training experience | Departments and academies |
| Duration | 8 weeks | 11 weeks | 12 months |
| Price (MYR) | RM 640 | RM 2,700 | RM 4,650 |
| Group size | Max 10 | Open | One institution |
| Lab hours | Self-directed | 9 hrs/week scheduled | Sandbox compute included |
| Assessment | Reproduction report + peer review | Deployed service + written review | Annual cohort performance report |
Standards Applied Across All Programmes
Participant Data Handling
Submission and contact data held under the Privacy Policy. Not shared with third parties for marketing. Institutional partner data handled separately under the partnership agreement.
Citation Standards
Where curriculum content draws on published research or industry frameworks, the source is named in the material. Participants can verify what they are being taught against the original.
Regular Curriculum Revision
Syllabi are reviewed and updated when the underlying field moves. The MLOps curriculum was last revised in January 2025 to incorporate updated deployment and monitoring practice from 2024 literature.
Output-Based Assessment
No programme uses attendance or quiz scores as the sole basis for completion. Each requires a substantive output that can be reviewed by the facilitator or peers.
Accreditation Transparency
Programmes are described precisely. No accreditation is claimed that is not formally held. Institutional partners receive written confirmation that formal recognition is their own responsibility.
Direct Responses
Enquiries go to the person responsible for the relevant programme. Response time target is two business days for individual enquiries and four business days for institutional enquiries.
Pricing
RM 640
per person · 8 weeks
- Published open curriculum
- Twice-weekly facilitated sessions
- Cohort capped at 10
- Peer review and reproduction report
RM 2,700
per person · 11 weeks
- 5 contact hours per week
- 9 scheduled lab hours per week
- Industry frameworks — sources named
- Deployed service + operational review
RM 4,650
per institution · 12 months
- Curriculum audit + licensed syllabus
- 3 instructor training weeks
- Sandbox compute, rubric, moderation
- Quarterly calls + annual report
Not Sure Which Fits?
Send us a note with your background and what you are hoping to work through. We will tell you which programme makes sense and what the prerequisites look like in practice.
Send an Enquiry