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Who it's for
Students
Graduate with proof, not just a degree.
Professionals
Be the one at work who actually knows AI.
Executives
Make the AI call with confidence.
Teams
Upskill the whole team, and measure it.
Educators
Teach what you know. Get paid fairly.
Platform
Pathfinder roadmaps
Your goal in, a week-by-week plan out.
Squad Mode
Study rooms with friends, a timer and a mood.
Verified Credentials
Proof you can do it, checkable in one click.
Teach & earn
Prove a topic, then get paid to teach it.
Ask the Library
Ask anything. Get the exact lesson.
Study tools
Flashcards, a notebook and a tutor that remember for you.
Resources
The library
Every course, module and topic.
AI of the Week
One development, explained.
Executive briefings
Twenty minutes on strategy and risk.
Paper Club
One paper a week, reproduced.
Office hours
AMAs, workshops, study halls.
Research Labs
Guided research, public showcase.
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Library
/
Machine Learning (Supervised + Unsupervised)
/
Machine Learning Foundations
topic
M02 路 Build: Project Understanding, Data Collection & Data Synthesis
From business problem to ML project (recap of EDA framing)
15 min
Data sources, collection and labels
15 min
What data synthesis is and when to use it
15 min
Generate synthetic data (3 methods)
15 min
Check synthetic data quality: fidelity, utility, privacy
15 min
Total: 1.3 h of applied study listed above.
M02 路 Build: Project Understanding, Data Collection & Data Synthesis 路 1x1labs.ai