Azure AI Engineer (AI-102) Readiness: Build, Manage, and Deploy AI Solutions on Azure
Signature Course No. 359 — A Signature AI Socratic Coaching Course.
No experience needed — your coach starts where you are.
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 Azure AI Engineer (AI-102) Readiness: Build, Manage, and Deploy AI Solutions on Azure 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.
An AI solution is an engineering artifact, not a demo. Most failures are not failures of model cleverness. They are failures of engineering judgment — a prebuilt service stretched past what it was built for, a custom model commissioned where a threshold would have done, a generative answer with no grounding and no evaluation, a key pasted into source code, a quota discovered in production, a confidence score treated as a guarantee. This course teaches the engineer's deciding sequence until it becomes reflex: name the workload, name the constraint that actually decides, pick the service whose built purpose matches, state the limit you are accepting, and state how you will know it works.
It starts with the job. The Azure AI Engineer Associate designs and implements AI solutions on Azure — the choices and the configuration are both yours. You will plan and manage real Azure AI resources, then build the classical services to working depth: Azure AI Vision, Language, Speech, Search, and Document Intelligence, before the generative layer on Azure OpenAI in Azure AI Foundry.
It works in two movements. First, Module 1 — Choose It, Build the Classical Services — work through Concepts 1–9, finishing with The Intake, Vision, and Search Build Plan; then, Module 2 — Generate, Deploy, and Operate It — work through Concepts 10–18, finishing with The Generative Deployment and Operations Plan.
Both capstones produce real artifacts — a complete build plan for Tamarind Cove Health Plan's intake, vision, and search streams, over 48,000 documents a month, 36,000 claim photographs, and an 8,400-document policy library; and a generative deployment and operations plan that grounds the member assistant in that library, deploys and secures the system, and gates go-live on evidence drawn from the workload itself.
The honesty standard is part of the course. This course prepares you for the Microsoft Certified: Azure AI Engineer Associate credential and its AI-102 exam; it does not promise that you will pass, it does not predict a score, and it confers no certification — only Microsoft certifies. What it promises is narrower and more useful: if you can do, cold and in writing, everything its Prove checks and capstones demand, you walk toward the exam carrying the exact skills the published blueprint names.
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.
Azure AI Engineer (AI-102) Readiness: Build, Manage, and Deploy AI Solutions on Azure 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 the job itself. Think of an AI feature you have used or seen shipped and say which of the five deciding moves — workload, deciding constraint, service match, accepted limit, evidence — was done weakest, and what that cost; say where your current knowledge sits, service by service, between naming, configuring, and defending a choice; describe a demo that impressed you and say what its input would look like in the worst decile of the real workload. 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 Intake, Vision, and Search Build Plan for Module 1 and The Generative Deployment and Operations Plan for Module 2 — that pull the whole course together, and earn the certificate.
What You'll Learn
Workload first, service second, safeguards and measurement always. Every skill in this course is the same discipline at a different layer: state what arrives and what must leave, name the constraint that actually decides, match the service to the job, write down the limit you are accepting, and prove it on material drawn from the real workload — including its worst decile.
Module 1 chooses and builds the classical services. The Role and the Blueprint; The Running System; Plan and Manage; Responsible AI and Content Safety; Vision Analysis and Custom Vision; Reading, Faces, and Video; Language Analysis and Translation; Speech and Conversational Language; Knowledge Mining with Azure AI Search — the planning, safeguards, and service craft the blueprint examines, each taught at the depth of what you configure, what you pass it, what it returns, and where its limits force a different choice.
Module 2 generates, deploys, and operates. Azure OpenAI Deployments; Prompting, Grounding, and Retrieval; Document Intelligence in Depth; Custom Models Done Properly; Deploy the Solution; Secure and Integrate; Monitor, Cost, and Quotas; Evaluate with Evidence; Readiness as Judgment — generation grounded in your own documents, deployment chosen by workload shape, identity and networking without shared secrets, and accuracy measured on test sets you built yourself.
And it counts readiness honestly throughout. Readiness is not a list of services you can name. It is judgment performed cold, on a fresh scenario, under the blueprint's constraints — which is exactly what every Prove check and both capstones demand.
What you will learn
- Plan and manage an Azure AI solution: select services, regions, and tiers, control access, and apply responsible AI and content safety
- Build computer vision solutions: image analysis, custom classification and object detection, OCR, and video analysis, within their stated limits
- Build natural language and speech solutions: text analysis, translation, question answering, conversational language understanding, and speech to text and text to speech
- Implement knowledge mining with Azure AI Search: indexes, skillsets, indexers, and ranking over your own content
- Build generative AI solutions with Azure OpenAI: model deployments, prompt design, grounding with retrieval, and fine-tuning decisions
- Deploy, secure, monitor, and evaluate Azure AI solutions: endpoints and containers, identity and networking, quotas and cost, and measured accuracy
Everything in the course
- All 18 concepts of Azure AI Engineer (AI-102) Readiness: Build, Manage, and Deploy AI Solutions on Azure, 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 Intake, Vision, and Search Build Plan and The Generative Deployment and Operations Plan
- 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 engineers who ship AI on Azure
Developers and engineers moving onto Azure AI — who can write code and call an API, and now need the service map, the configuration judgment, and the blueprint depth the associate credential examines; and solutions and cloud engineers who design workloads and must defend a service choice, a tier, and a safeguard to a reviewer who will ask why.
AI-102 candidates — who want readiness built on performed skill, not on memorized question banks: every concept here ends in a fresh scenario you must handle, not a fact you must recite.
Technical leads reviewing AI designs — who need to spot the ungrounded answer, the leaked key, the missing evaluation, and the wrong service before production does it for them. This course assumes the fundamentals — what a resource group is, what a region is, what an API key does — and that you can read a simple request and response.
Prefer to learn live and in person? The same material anchors Cognosco's one-day programs — browse the in-person catalog.
Start with The Role and the Blueprint
$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.
Before you enroll
What is a Socratic coaching session?
A conversation, not a video. Your coach asks a question; you answer — out loud by voice, or by typing — and the coach responds to what you said: naming the misconception it hears, affirming what you got right, and asking the next question. You advance only when you have mastered each concept, so a finished course means the learning held.
How long does it take — and how long do I have?
About 30 minutes per concept. Learn in sittings of any length; your progress is saved as you go. You have a full year from purchase to finish, and you can revisit and retake within that year.
What does the certificate verify?
That you completed every concept and both capstones of this course. Anyone can confirm a Cognosco certificate online — enter its certificate ID on our verification page.
What if it isn't for me — what are the refunds?
If you have not started, cancel for a full refund within seven days of purchase. Once you have started, there is no cash refund — stop before finishing and we credit the full amount you paid toward any other course in the library (credit valid one year from your original purchase). Once you complete the course, no refund or credit applies.
More Signature Courses are coming
Azure AI Engineer (AI-102) Readiness: Build, Manage, and Deploy AI Solutions on Azure is Signature Course No. 359. Leave your email and we'll send you news of future Signature Courses and Lighthouse updates as they are announced — nothing else.