Aimasteryhub

Catalogue 2026

Six programmes, each ending in something you can run on Monday.

Public lines meet in the Bain Street studio on weekday evenings, with a Saturday clinic. Private sprints run on your floor. Fees below are in Singapore dollars and cover instruction, sample data and six months of cohort notes.

Studio meeting

How to read this

Structure of the catalogue

Each public programme lists format, length, level, the artefact you assemble, and the modules in order. Seats are twelve. You work on one workflow for the whole run so the evaluation set stays stable. Online participants join the same Wednesday block by live stream and keep the same deliverables.

Applied LLM Foundations

6 weeks · evenings 19:00–22:00 · Saturday clinic · foundational · S$1,980

You assemble a small assistant with a prompt contract, a logged API wrapper, and an evaluation set of 80–150 labelled cases. The Monday artefact is a script that returns a structured answer and a score against last week’s baseline.

  • Prompt as contract. Inputs, outputs, refusals and a version number in the file name.
  • Evaluation set first. You write cases before you chase a clever phrasing.
  • Logging and cost. Token counts and latency on a 50-item slice.
  • Structured outputs. JSON schemas the next tool can consume.
  • Regression after edits. A one-page score table for prompt versions 1 through n.

Automation Studio: Agents & Workflows

8 weeks · evenings 19:00–22:00 · Saturday clinic · intermediate · S$2,480

You build a short agent graph with tool calls, a human checkpoint, and a dead-letter queue. The shipped artefact is a workflow that can pause, retry, and show an operator why it stopped.

  • Task graph on paper. Nodes, tools, and the human gate before any framework.
  • Tool wrappers. One function per side effect, with timeouts you can read.
  • State and queues. What is stored, what is replayed, what is dropped.
  • Failure log. A table of the last 40 errors with the prompt version attached.
  • Operator view. A minimal screen or notebook that shows current jobs.
  • Handover. A runbook of 2 pages for the person covering Saturday.

Retrieval & Data Engineering

7 weeks · evenings 19:00–22:00 · Saturday clinic · intermediate · S$2,880

You index a corpus you control, usually 400–2,400 documents, and measure retrieval on a held-out question set. The artefact is a search path that returns passages with citations, plus the notes on chunk size that actually moved the score.

  • Corpus hygiene. Deduping, licences, and what never leaves the laptop.
  • Chunking trials. Three sizes scored on the same 40 questions.
  • Embeddings and keyword mix. Hybrid retrieval with a recorded blend.
  • Citations. Every answer points at a passage you can open.
  • Drift checks. A monthly re-score recipe even if you only run it once in class.
  • Access notes. Who may query the index after the cohort.

Model Evaluation & Guardrails

5 weeks · evenings 19:00–22:00 · Saturday clinic · intermediate · S$3,400

You write release criteria for a model-backed tool: gold set, refusal policy, logging, and a go/no-go sheet. The artefact is an evaluation pack a second person can rerun without you in the room.

  • Gold and shadow sets. What is labelled, what is held back.
  • Task metrics. Time, match rate, escalation rate. Model “accuracy” sits behind the task.
  • Refusal and leakage. Prompts that must not answer, with tests.
  • Logging minimum. Prompt version, model alias, latency, outcome.
  • Release sheet. The five numbers a lead signs before a wider rollout.

AI for Operations Leads

4 weeks · evenings 19:00–22:00 · non-technical · S$3,600

You scope a workflow, write the evaluation questions, and leave with a brief a developer or vendor can price. Studio time uses spreadsheets, sample tickets and structured notes rather than a production repository.

  • Workflow map. Volume, cycle time, and the 20% of cases that consume the week.
  • Vendor questions. Data handling, eval access, and who owns the prompt.
  • Reading a score. Baseline versus model, on a set you can explain.
  • Pilot design. Two-week sandbox, 100 cases, named reviewer.
  • Handover pack. Risks, owners, and the metric you will watch in month two.

Team Enablement Sprint

3 days · on your site or in Bras Basah · 8–16 people · private quote

A closed cohort for one team and one workflow. Day one freezes the evaluation set. Day two builds the thinnest path that scores. Day three writes the runbook and the list of items that will wait for a later programme. Quote depends on group size, location and whether sample data must be synthesised on site.

  • Pre-sprint call. Data rules, laptop setup, and the metric the sponsor cares about.
  • Shared repo or shared folders. One artefact the whole room can open.
  • Role split. Operator, reviewer, builder. Each seat has a job.
  • Exit brief. What shipped, what failed, what needs a 6-week line afterwards.

Preparation

Kit and requirements

Bring a laptop you administer. Public programmes assume you can install a current browser, a code editor, and the CLI for one model provider. API keys stay in your account; Aimasteryhub does not issue shared keys. Budget a modest usage cap. Most foundation weeks stay under a mid-two-figure USD spend if you keep the evaluation slice to a few hundred calls.

The studio supplies desks, displays, wireless network, whiteboards, and the sample corpora used in demos. We do not lend laptops. If your employer blocks local Python or Node, say so on the enrolment call so we can plan a notebook-only path for that seat.

Closed groups

Private cohorts for teams

The Team Enablement Sprint is the three-day format on the client’s floor or in Bain Street, for eight to sixteen people. Longer private copies of the public lines are possible when a department wants the same syllabus with internal examples. We work on anonymised or synthetic sets. Confidential production data stays off the studio machines.

A typical request is a support or finance team that already has labelled history and wants a router or a reconciler they can show in week two. Write to [email protected] with headcount, city, and the workflow in one paragraph.

Choosing

Not sure which line fits

If you will type prompts, keep a spreadsheet of cases, and want a script you can rerun, start with Applied LLM Foundations. If your week is already full of tickets, files or mail that must move without you, look at Automation Studio. If the pain is “the documents exist and nobody can find the clause”, look at Retrieval & Data Engineering.

If your job is to approve a vendor and brief a builder, take AI for Operations Leads. If you already have a prototype and the argument is about safety and scores, take Model Evaluation & Guardrails. A 20-minute call will sort the edge cases.