AI Terms Managers Need to
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Speak AI like you mean it

Master the 50+ AI terms that actually come up in meetings, vendor pitches, and executive briefings — so you can lead AI conversations with confidence, not anxiety. No technical background needed.

25 lessonsAI-adaptiveCancel anytimeLearn anywhere
AI Terms Managers Need to Know

You don't need to become an AI expert — you need to become the manager who knows exactly what questions to ask, and that's a skill I can absolutely give you.Freddy Foster

What you'll learn

What you'll be able to do

  • Define and correctly use 50+ essential AI terms in meetings, reports, and strategy discussions
  • Evaluate AI tool proposals from vendors or technical teams without being misled by buzzwords
  • Ask the right questions when your team presents an AI-driven project or recommendation
  • Distinguish between hype and genuine capability when reading AI news or executive briefings
  • Communicate AI concepts clearly to both leadership above and direct reports below
  • Build a personal AI vocabulary reference you can apply immediately on the job

How it works

A school that adapts to you

This isn't a set of static videos. Every lesson is generated live and tuned to where you actually are.

We learn your level

A quick placement check tailors your starting point so you're never bored or lost.

Lessons adapt as you go

Each lesson is written for your pace and your goal, adjusting as your skills grow.

Your AI coach keeps you moving

Checkpoints, feedback, and gentle nudges turn progress into a real result.

The curriculum

What's inside your school

6 modules · 25 lessons

1

The AI Landscape: What Managers Actually Need to Know

Establishes a clear mental map of AI, its major branches, and why the vocabulary matters for managerial decision-making.

  • 1.1Why AI Literacy Is Now a Management SkillIncluded
  • 1.2AI, Machine Learning, and Deep Learning — What's the Difference?Included
  • 1.3A Quick Tour of AI in the Real WorldIncluded
  • 1.4How to Build Your Personal AI Vocabulary ReferenceIncluded
2

Core AI Concepts Every Manager Must Recognize

Covers the foundational technical terms — models, data, training, and algorithms — explained entirely through a business lens.

  • 2.1What Is a Model — and Why Should You Care?Included
  • 2.2Data: Input, Output, and Why Quality MattersIncluded
  • 2.3Algorithms, Parameters, and the 'Black Box'Included
  • 2.4Supervised, Unsupervised, and Reinforcement LearningIncluded
  • 2.5Accuracy, Precision, and Performance MetricsIncluded
3

Generative AI and Modern Buzzwords Decoded

Unpacks the vocabulary surrounding today's most-hyped AI technologies, from large language models to prompts and hallucinations.

  • 3.1What Is Generative AI — and What Can It Actually Do?Included
  • 3.2Large Language Models, GPT, and Foundation ModelsIncluded
  • 3.3Prompts, Fine-Tuning, and RAG: Terms You'll Hear in Every MeetingIncluded
  • 3.4Hallucinations, Guardrails, and AI ReliabilityIncluded
  • 3.5Hype vs. Reality: Reading AI Headlines Like a ProIncluded
4

Evaluating AI Tools and Vendor Proposals

Equips managers to assess AI products, scrutinize vendor claims, and avoid being misled by jargon-heavy pitches.

  • 4.1The Questions Every Manager Should Ask Before Approving an AI ToolIncluded
  • 4.2Spotting Buzzword Inflation in Vendor PitchesIncluded
  • 4.3Understanding AI Pricing Models and Total Cost of OwnershipIncluded
  • 4.4Responsible AI, Explainability, and Compliance VocabularyIncluded
5

Leading AI Conversations Up, Down, and Across the Organization

Builds the communication skills to translate AI concepts fluently for executives, direct reports, and cross-functional peers.

  • 5.1Talking AI with Senior Leadership: Framing Value, Not TechnologyIncluded
  • 5.2Guiding Your Team Through an AI-Driven ProjectIncluded
  • 5.3Communicating AI Limitations and Risks Without Killing MomentumIncluded
  • 5.4Cross-Functional AI Vocabulary: Speaking Data Science, IT, and LegalIncluded
6

Putting It All Together: Your AI Vocabulary in Action

Consolidates all 50+ terms through applied scenarios, a completed personal reference, and a confidence-building capstone.

  • 6.1Real-World Scenarios: Apply Your Vocabulary Under PressureIncluded
  • 6.2Your Complete AI Glossary: Finishing and Formatting Your ReferenceIncluded
  • 6.3Staying Current: How AI Vocabulary Keeps EvolvingIncluded

Who it's for

Is this you?

The Operations Manager

Fielding AI tool proposals from vendors and needs to evaluate them intelligently without relying entirely on IT.

The Marketing Director

Using AI-generated content tools daily but wants to speak confidently about AI strategy in leadership meetings.

The HR Leader

Navigating AI in hiring and performance tools and needs to understand compliance and responsible AI vocabulary.

The Finance Manager

Expected to weigh in on AI investment decisions and needs to understand what they're actually approving.

The Product Manager

Collaborates with data science and engineering teams daily and wants to close the vocabulary gap for good.

The Newly Promoted Senior Manager

Just stepped into a role with more strategic responsibility and knows AI fluency is now part of the job.

Questions

Frequently asked

Your teacher

A note from your teacher

Freddy Foster

Freddy Foster

Let me guess where you are right now.

You're in meetings where people throw around terms like "foundation models," "RAG pipelines," or "responsible AI" — and everyone else seems to nod like it makes perfect sense. You read the executive briefings on AI strategy and understand the business goal, but the middle part, the actual AI part, feels like it's written in a foreign language. And you're starting to wonder whether not knowing this stuff is going to quietly hold you back.

I've worked at the intersection of business leadership and technical teams for years, and I can tell you: this feeling is nearly universal among managers right now. It's not a knowledge gap that reflects badly on you. It reflects the pace of change. AI literacy has become a management skill almost overnight, and nobody handed most managers a curriculum.

That's exactly why I built this school — and why I built it the way I did. Not as a technical primer for aspiring data scientists, but as a practical vocabulary toolkit for working managers. Everything here is grounded in the situations you actually face: a vendor pitching an AI tool that sounds impressive but raises questions you can't quite articulate. A direct report presenting a recommendation from a model you've never heard of. A board-level conversation about AI risk where you need to hold your own. The curriculum walks you through the concepts that matter — models, training data, generative AI, hallucinations, explainability, pricing structures — and connects every single one to real decisions in real organizations.

Here's what I want you to know: you don't need to become an AI expert. You need to become the manager who understands enough to lead. To ask the right questions. To spot when a vendor is overselling and when a risk is being undersold. To translate between your technical team and your senior leadership without losing the thread in either direction. That's a learnable skill — and it's exactly what this school teaches.

By the time you finish, you'll have a working vocabulary you can use immediately, a personal AI glossary you've built yourself and can keep updating, and a confidence in AI conversations that you probably don't feel right now. That's the whole goal. Come in curious, leave capable. I'll be with you the whole way.

Freddy Foster

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  • 6 modules, 25 lessons
  • AI-adaptive lessons tuned to your level
  • Quizzes & checkpoints to lock in progress
  • Your own AI learning coach
  • Learn on any device, at your pace
  • Full access for as long as you're subscribed