LEARNING PATH PLANNER

EVERY COURSE
IS A STATION.
LEARNING IS
THE LINE BETWEEN.

Catalogue search hands you a pile of stations and wishes you luck. Waypoint builds the line — working out which skills stand between you and where you want to be, then ordering the journey so you never arrive somewhere you are not ready for.

Or pick a destination yourself →No sign-up, plots in a second.

Hover a station to see the skill it represents and the hours it takes.
  • DATA ANALYSIS
  • WEB DEVELOPMENT
  • FOUNDATIONS
  • INTERCHANGE

0.0% PREREQUISITE VIOLATIONS. 93.0% SKILL GAP CLOSED. 0.392 AGREEMENT WITH EXPERT. 126 RESOURCES SURVEYED. 10 EXPERT-LABELLED ROUTES. 181 TESTS PASSING. Every figure is measured, not claimed.

A ROUTE, PLOTTED

Starting from nothing, aiming at Deep Learning Basics at a working professional level.

STOPS
11
HOURS
114
VIOLATIONS
0
REACHES GOAL
YES
  1. 3Blue1Brown: Essence of Linear Algebra

    5h

    3Blue1Brown · difficulty 2/5 · Linear Algebra Basics 0▸3

    OPEN ↗
  2. StatQuest with Josh Starmer

    15h

    StatQuest · difficulty 2/5 · Descriptive Statistics 0▸3 · Inferential Statistics 0▸3 · Supervised Learning 0▸2 · Model Evaluation 0▸2

    OPEN ↗
  3. Kaggle Learn: Intro to Deep Learning

    5h

    Kaggle · difficulty 3/5 · Deep Learning Basics 0▸3

    OPEN ↗
  4. Kaggle Learn: Python

    5h

    Kaggle · difficulty 1/5 · Python Basics 0▸3 · Python Data Structures 0▸2 · Python Functions & Modules 0▸2

    OPEN ↗
  5. Kaggle Learn: Pandas

    4h

    Kaggle · difficulty 2/5 · Pandas DataFrames 0▸3

    OPEN ↗
  6. scikit-learn: Getting Started

    2h

    scikit-learn · difficulty 2/5 · Scikit-learn Basics 0▸2

    OPEN ↗
  7. Kaggle Learn: Intermediate Machine Learning

    5h

    Kaggle · difficulty 3/5 · Scikit-learn Basics 2▸4 · Model Evaluation 2▸3 · Supervised Learning 2▸3

    OPEN ↗
  8. NumPy: The Absolute Basics for Beginners

    4h

    NumPy · difficulty 2/5 · NumPy Arrays 0▸3

    OPEN ↗
  9. Seeing Theory

    4h

    Brown University · difficulty 2/5 · Probability Basics 0▸3

    OPEN ↗
  10. freeCodeCamp: Scientific Computing with Python

    25h

    freeCodeCamp · difficulty 2/5 · Python Functions & Modules 2▸3 · Python Data Structures 2▸3

    OPEN ↗
  11. Practical Deep Learning for Coders

    40hINTERCHANGE

    fast.ai · difficulty 3/5 · Deep Learning Basics 3▸4

    OPEN ↗

BOTH ROUTES ARE REAL PLANNER OUTPUT AGAINST THE LIVE CORPUS

HOW THE LINE IS BUILT

Four mechanisms, none of them a chat wrapper. The language model reads your goal and phrases the reasoning; it never chooses a course, never decides an order, and never sees the catalogue.

01

SURVEY

You describe the destination in your own words. It compiles into concrete skills and target levels against a canonical graph — never invented, only selected.

02

MEASURE

Your position minus the destination gives a gap, expanded across every prerequisite. Retrieval matches that gap, not your sentence, against what each resource teaches.

03

PLOT

Beam search over the prerequisite graph. Only resources you are ready for are ever considered, so an impossible ordering cannot be produced — not filtered out, never generated.

04

RE-ROUTE

Tell it a course did not work. Mastery moves, the line is re-plotted around it, and the diff names exactly what changed and why it changed.

MEASURED, NOT CLAIMED

Scored against 9 of 10 learning paths a human expert wrote by hand, alongside the semantic search this is meant to beat. Both saw the same catalogue of 126 resources and the same embeddings.

0.0%

similarity search: 49.0%

PREREQUISITE VIOLATIONS

93.0%

similarity search: 64.7%

SKILL GAP CLOSED

0.392

similarity search: 0.168

AGREEMENT WITH EXPERT

0.459

similarity search: 0.111

ORDERING CORRELATION

The last figure is the one worth staring at. A correlation of 0.111 means the baseline's ordering is indistinguishable from shuffling the results. It finds relevant courses and then hands them to you in an order nobody could learn from.

Measured 30 August 2026 · the baseline searches with the same embeddings we do