IBM AI Engineering
Signature Course No. 215 — A Signature AI Socratic Coaching Course.
A New Kind of Learning
Socratic coaching, delivered by an agentic AI coach.
Not a course you watch. An AI coach you work with.
The Lighthouse Coach begins by discovering how you think about the subject, teaches what is missing, and gives you realistic practice before asking you to prove that you can use it. You may test out of concepts you already understand, while capstones turn the learning into a practical plan, decision, conversation, or other real-world result.
The curriculum is deliberately authored; the AI delivers it through coaching. It is not an AI randomly generating lessons.
A coach that teaches by asking — not by lecturing
The Lighthouse Coach is an AI Socratic coach built on Cognosco Learning's IBM AI Engineering course, in the AI at Work category. It does not play videos at you. It holds a conversation: it asks you a question, listens to your answer, names the misconception it hears, affirms what you got right, and asks the next question — the way a great coach works in the room.
A model is the smallest part of an AI system. Around it sits everything that decides whether the system works in the world: a specification someone signed, data that arrives on time and means what it meant last month, an evaluation that measures the cases that matter, a serving path that answers inside a budget, a release process that can be undone, monitors that notice when the world moves, and a record that lets a stranger reconstruct why the system said what it said on a given Tuesday.
First you engineer the system before the model ships. The brief before any fitting; data as an engineered supply chain with contracts, validation, and lineage; fitting-data discipline and reproducible fitting against honest baselines; evaluation written as a contract with slices and an error budget; and the compute, serving, and money budgets computed from stated inputs.
Then you operate it in production. Releases in stages with a rehearsed way back; pipelines held to their service levels; monitoring across inputs, outputs, and outcomes with drift answered from a decision tree; incidents run by species and accounted by blast; scaling inside a cost ceiling with degradation designed in advance; security, privacy, and governance engineered in; and the lifecycle run from handover to retirement.
It works in two movements. First, Module 1 — Engineering the System Before the Model Ships — work through Concepts 1–9, finishing with The Pre-Production Dossier; then, Module 2 — Operating AI in Production — work through Concepts 10–18, finishing with The Year in Production.
Both capstones produce real artifacts — The Pre-Production Dossier, the complete pre-production evidence for Forgepoint Industrial Systems' Line 2 carton-inspection system, closing with a gate recommendation; and The Year in Production, a one-year operations and governance plan for the inspection system and the maintenance-triage system beside it, closing with a signature block under the engineer's standard.
The honesty discipline is part of the course. The engineering is taught vendor-neutrally: platform specifics are version-sensitive, named product facts are framed in place with a direction to check the current documentation, and no vendor claim or market statistic is stated anywhere as a finding. Every worked figure is the running company's own, shown with its inputs, or a labelled illustrative magnitude.
The course is self-paced and always on — roughly 30 minutes per concept, about 9 hours in full, taken in as many sittings as you like. You can type your answers, or talk out loud: the Voice Coach speaks its questions and listens to your spoken replies. Learners who already know the material can test out concept by concept.
IBM AI Engineering is part of The Lighthouse Signature Series — the online counterpart to the one-day, in-person learning Cognosco Learning has delivered since 2002.
Course Facts
One full concept, coached end to end — free: verify your email and we’ll send you a link to start.
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Diagnose → Learn & Practice → Prove → Capstone
Every learner moves through the same discipline a Cognosco instructor would insist on in the room.
Diagnose
The Coach starts where the course starts: with what you actually bring. Every engineered system begins with a brief — the decision it supports, what it will be fed, how fast and how reliably it must answer, what each kind of wrong answer costs, and what evidence will count as proof. Every concept opens with three questions that locate where you actually stand, and your answers shape how deeply the Coach works the concept with you. Everyone begins with Module 1 — no skipping the foundations you only think you have.
Learn & Practice
Work each concept in conversation with the Coach — spoken or written — then practice it against realistic situations until it holds up.
Prove
Every concept ends in proof: answer the check cold and demonstrate the skill. Know it already? Test out and take credit immediately.
Capstone
Finish with two capstones — The Pre-Production Dossier for Module 1 and The Year in Production for Module 2 — that pull the whole course together, and earn the certificate.
What You'll Learn
No fitting before the brief. Specify an AI system as an engineering brief — decisions, budgets, failure costs, and acceptance tests — and engineer the pipelines that feed it, with contracts, lineage, validation, and freshness guarantees.
Module 1 builds the system that deserves to ship. Fitting-data discipline, reproducible fitting against baselines, evaluation as a signed contract, and deep-learning fitting and inference inside compute, memory, latency, and cost limits.
Module 2 keeps it deserving its place. Staged releases with rollback, production pipelines against their service levels, three-layer monitoring and drift response, incidents accounted by blast, and scaling with degradation designed in advance.
And it closes with a signature. Security and privacy engineered in, governance an auditor can reconstruct from, the lifecycle run to a clean end — and the AI engineer's standard you sign for all of it.
What you will learn
- Specify an AI system as an engineering brief — decision, budgets, failure costs, and acceptance tests — before any model is fitted, and engineer its data pipelines with contracts, lineage, validation, and freshness guarantees
- Fit models as an engineering discipline — baselines, leakage control, fully reproducible runs — and evaluate them as a contract: metrics tied to decisions, slice analysis, and error budgets
- Engineer deep-learning fitting and inference inside compute, memory, latency, and throughput limits, and deploy and serve models safely — release patterns, rollback, scaling, and graceful degradation
- Operate AI systems over their whole lifecycle: monitoring, drift response, incidents, cost control, governance, and retirement — closing with the engineer's standard you sign
Everything in the course
- All 18 concepts of IBM AI Engineering, in 2 modules
- A starting-point check first — the Coach finds where you actually stand before teaching
- Learn, Practice, Prove for every concept — no passive video watching
- A test-out on every concept: prove you know it and move on
- The Voice Coach: talk with the Coach out loud — it speaks, listens, and replies
- A personal Learner Record of your work across the course
- Two capstone exercises: The Pre-Production Dossier and The Year in Production
- A printable session summary whenever you pause
- The Lighthouse Coach completion certificate (Signature Series)
- Your progress is saved as you go — stop anytime, resume where you left off
Built for people who run models in production
Software engineers moving into AI work — who already know how to ship systems and now need the discipline that models add: data that changes meaning, behaviour that degrades silently, and evaluation that never quite ends.
Machine-learning practitioners — who can fit a model in a notebook and need the engineering around it: pipelines, serving, monitoring, release discipline, and cost control.
Platform and operations engineers, and technical leads and engineering managers — who inherit AI systems in production and run them to a standard, and who approve AI systems, set their budgets, and sign for their risks. The course assumes you can read code, follow a data flow, and do arithmetic with units; it assumes no prior production AI experience.
Prefer to learn live and in person? The same material anchors Cognosco's one-day programs — browse the in-person catalog.
Start with The Pre-Production Dossier
$195 — introductory price. One payment. No subscription, no password to manage.
Here is exactly what happens when you enroll:
- Pay securely with Stripe — you are taken straight into the course
- Create your learner profile and begin the Module 1 starting-point check
- Save the access key you are given — it restores your enrollment on any device
- Learn at your pace; your progress is stored in your browser on your device
For the full voice experience, use Chrome and allow the microphone when asked. Typing your answers works everywhere, all the time. Questions before you enroll? Email hello@cognoscolearning.com.
More Signature Courses are coming
IBM AI Engineering is Signature Course No. 215. Leave your email and we'll send you news of future Signature Courses and Lighthouse updates as they are announced — nothing else.