Speak AI fluentlyin your next meeting
Bite-sized lessons on ML, LLMs, RAG, and product decisions — so terms like embeddings, tokens, and evals finally make sense.
Let's start with Lesson 1~2 min · 12 lessons · jump in as guest
12
Lessons
4
Units
81
Questions
How it works
Learn fundamentals
ML, neural nets, and how LLMs actually work
Practice with scenarios
Real workplace examples — vendor calls, PRDs, demos
Apply at work
Sound confident in reviews and make better AI decisions
AI Fluency
From ML fundamentals to LLMs, RAG, and product decisions — practical fluency for the AI era.
Unit 1
FundamentalsHow ML Works
Fundamentals: what machine learning is, how models learn, and why data quality matters.
Supervised vs Unsupervised
6 questions
Training Data & Overfitting
7 questions
Unit 2
Key conceptsNeural Networks & LLMs
Important concepts: neural nets, transformers, tokens, and how ChatGPT-style models work.
Neural Network Basics
7 questions
Transformers & Attention
7 questions
LLMs, Tokens & Training
7 questions
Unit 3
PracticalEmbeddings, RAG & Safety
Practical skills: semantic search, RAG, prompting, hallucinations, and responsible AI.
Embeddings & Vector Search
6 questions
RAG & Prompting
7 questions
Hallucinations & AI Safety
6 questions
Unit 4
At workAI at Work
Product vocabulary, vendor evaluation, and build-vs-buy decisions — fluency for the meeting room.
AI Product Vocabulary
7 questions
Evaluating AI Vendors
7 questions
Build vs Buy & AI in PRDs
7 questions
Ready to stop nodding along?
Let's start with Lesson 1