By invitation Access by access key.

Learn AI by doing the work, not watching it.

132 topics. 89.6 hours. A shared core for everyone, a track for your job, and a Prompt Lab that scores what you write out of 100 and tells you exactly what is missing.

Access is by invitation. Sign in with the Google or Microsoft account you already have, then enter the access key an administrator issues you.

Why this exists

Watching a video is not a skill.

You can finish ten hours of AI content and still freeze in front of an empty prompt box. Passive courses measure attendance. This one measures work.

  • Video courses hand you a certificate for pressing play. Nothing you watched was ever checked.
  • Nothing tells you when a prompt is bad. You get a mediocre answer and assume that is just what AI does.
  • Here you write, submit and get scored. Quizzes, workbooks, hands-on projects and a Prompt Lab that grades six named dimensions and shows you the stronger version, line by line.

The curriculum

One shared core, then a track that fits your job.

Five phases over about 17 weeks. Everyone starts in the same place; the track you add depends on whether your output is code, documents or decisions — or which cloud and hardware you build on.

Everyone takes the same core: 40 topics · 24.7 h Foundations, prompting, model architectures, deployment and responsible AI — in plain English, whatever your role. Then you add one of these.

Prompt Mastery Track

Everyone — the fastest payback for any role

12Topics

5.8Hours

The habits that separate a vague request from a prompt that returns work you can actually use. Additive — open to all, whichever other track you pick.

Example topics

  • The Anatomy of a Great Prompt: Role, Task, Context, Format, Constraints
  • Why Vague Prompts Fail
  • Few-Shot Examples: Show, Don't Just Tell
  • Prompt Anti-Patterns and Fixes

With the core: 52 topics · 30.4 h

Engineering Track

Developers, testers, architects, data engineers

20Topics

16.4Hours

From calling an LLM API to shipping something you would put in front of customers: structured outputs, RAG, agents, evaluation, tracing, cost and security.

Example topics

  • Structured Outputs, JSON Schema & Tool Schemas
  • Building a RAG Pipeline End to End
  • Agent Architectures & Tool-Calling Loops
  • LLM Security for Engineers: Injection, Exfiltration & Sandboxing

With the core: 60 topics · 41.1 h

Business & Builder Track

PMs, analysts, admins, marketing, ops, leadership

20Topics

11.8Hours

Turn AI into an everyday work habit — drafting, summarizing, analysing research and spreadsheets, role playbooks, no-code automation and the privacy rules that keep you safe.

Example topics

  • The 5-Part Prompt Recipe That Actually Works
  • Summarizing Long Documents and Meetings
  • Prompt Playbook for Product Managers
  • What NOT to Put Into AI Tools: Data, Privacy and Policy

With the core: 60 topics · 36.5 h

AWS AI Track

Engineers, architects and analysts working on AWS

10Topics

7.8Hours

The AWS generative AI stack end to end: foundation models through Amazon Bedrock, custom models on SageMaker AI, RAG with Knowledge Bases, agents on AgentCore, and the guardrails a security review will ask about.

Example topics

  • Amazon Bedrock: Foundation Models as a Service
  • Knowledge Bases: Managed RAG on AWS
  • Production Agents with Bedrock AgentCore
  • Bedrock Guardrails & Responsible AI on AWS

With the core: 50 topics · 32.4 h

Azure AI Track

Developers, data engineers and IT professionals in Microsoft shops

10Topics

7.6Hours

Microsoft's AI platform as it stands today: Microsoft Foundry and its model catalogue, grounding with Azure AI Search, prompt and hosted agents, Content Safety, and Entra-based governance.

Example topics

  • Microsoft Foundry: The Model Catalogue
  • Grounding with Azure AI Search
  • Prompt Flow and Hosted Agents
  • Content Safety & Entra Governance

With the core: 50 topics · 32.2 h

Google Cloud AI Track

Engineers, analysts and ML practitioners on Google Cloud

10Topics

7.7Hours

Google Cloud's AI surface: Gemini and Model Garden, Vertex AI Vector Search, grounding and citations, the open-source Agent Development Kit, BigQuery ML and responsible AI controls.

Example topics

  • Gemini and the Vertex AI Model Garden
  • Vertex AI Vector Search
  • Agents with the Agent Development Kit
  • BigQuery ML for Analysts

With the core: 50 topics · 32.3 h

NVIDIA AI Track

Platform engineers, ML engineers and anyone self-hosting models

10Topics

7.9Hours

One layer below the managed clouds: how GPUs and VRAM constrain AI, deploying models as NIM microservices, training and fine-tuning with NeMo, self-hosted RAG, and programmable safety with NeMo Guardrails.

Example topics

  • GPUs, VRAM and What Actually Limits Inference
  • Deploying Models as NIM Microservices
  • Fine-Tuning with NVIDIA NeMo
  • Programmable Safety with NeMo Guardrails

With the core: 50 topics · 32.6 h

The Prompt Lab

Two prompts. Same request. 86 points apart.

You write a prompt for a real work scenario. Six fixed checks score it out of 100 — published rules, the same for everyone, run in plain code rather than a model's opinion. Then you see the stronger version and where every point went.

Exercise: Write a Leadership Status Update. Your VP reads about 15 of these a month and skims each one in under a minute, so any line that does not change a decision gets cut.

What most people write 7 words · scored in milliseconds

14
Basic

Write a status update for my project.

Six-dimension rubric

Role & context0/20

Task clarity14/20

Specificity & constraints0/20

Format & structure0/15

Audience & tone0/15

Examples & evidence0/10

What the Lab teaches you to write All six dimensions covered

100
Expert

You are a project lead writing the monthly update for your VP.

Context: She reads about 15 of these a month and skims each one in under a minute, so any line that does not change a decision gets cut. My raw notes for the month are pasted at the end.

Task: Write the monthly status update for this project from those raw notes.

Constraints:
- No more than 200 words in total, with 2 to 3 bullets under each heading.
- A severity label (High/Medium/Low) on every risk, and a deadline on every ask.
- Avoid filler openers such as "as you may know", and do not report progress that is not in the notes.

Output format: three bold headings — Progress, Risks, Asks — each with short bullets, then a "Bottom line" of no more than three sentences.

Audience and tone: written for one busy VP rather than the wider team; direct, factual and unpolished, in plain English with no jargon.

Grounding and example: use only the notes below, and where a number is missing say so instead of estimating. A good Progress bullet reads: "Shipped the redesigned onboarding flow; early data shows 18% faster time-to-first-action for new users."

Six-dimension rubric

Role & context20/20

Task clarity20/20

Specificity & constraints20/20

Format & structure15/15

Audience & tone15/15

Examples & evidence10/10

10 Prompt Lab exercises 6 scored dimensions 4 bands: Basic → Developing → Strong → Expert Every exercise ships with a weak sample and a strong sample, so you can see the gap before you close it.

What's inside

Everything, counted.

No marketing rounding. These are the actual contents of the platform today.

132Topics across all seven tracks

89.6 hOf content if you did everything

396Quiz questions

57Glossary flashcards

5Workbooks

6Hands-on projects

AI instructorAsk questions on any topic, in context

Progress trackingHours, quiz scores and certificates, recorded

Structured as 5 phases over about 17 weeks — take it at that pace or go faster. Your progress is saved either way.

How it works

Four steps. Starts in under a minute.

There is nothing to install and nothing to configure — you just need an access key.

  1. Sign in

    Use the Google or Microsoft account you already have, then enter your access key. No new password to invent.

  2. Pick your track

    Prompt Mastery, Engineering, Business & Builder, or one of the cloud and hardware tracks — AWS, Azure, Google Cloud and NVIDIA. The 40-topic core is yours either way, and you can change track later.

  3. Learn and practise

    Read the lesson, take the quiz, work the workbook, build the project, then score a prompt in the Lab. Ask the AI instructor when you get stuck.

  4. Track your progress

    Hours, quiz scores, prompt scores and certificates are recorded as you go, so improvement is a number rather than a feeling.

Getting in

How to get access

Access to the courses is by invitation. Sign in with your Google or Microsoft account, then enter the access key an administrator gives you. If you do not have a key yet, contact your administrator to request access.

Access by invitation. Request yours.

Sign in with your Google or Microsoft account, then enter the access key your administrator issues you.

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