Incoming ML students
Use it before the first serious lecture
Refresh vectors, derivatives, probability, NumPy, and validation before those ideas are woven into model-building.
Pre-course
Readiness Arcade
A brief warmup for the math, Python, and evidence habits that prepare you to learn machine learning. This is neither a course nor a gatekeeping exam.
Who it helps
For learners who want a refresher on fundamentals
This arcade is for people who want to calibrate their math, code, and evaluation habits before venturing into learning machine learning.
Data science learners
Bridge from data work to ML
Move from tables, plots, and scripts toward distances, splits, metrics, and evidence statements.
Self-study learners
Self-diagnose
Use the start screen to choose what to practice.
Jupyter setup
Create a clean environment
The provided notebook is lightweight but you can setup a small conda environment with JupyterLab, NumPy, and Matplotlib to keep it clean.
Step 1
Install conda if you do not already have it
Miniforge, Miniconda, or Anaconda all work. After installation, open a fresh terminal so the conda command is available.
conda --versionStep 2
Create a small environment
The notebook uses NumPy and Matplotlib, plus JupyterLab for running cells interactively.
conda create -n readiness-arcade python=3.11 jupyterlab numpy matplotlibStep 3
Activate it
Activation makes sure the notebook uses the packages from this clean environment.
conda activate readiness-arcadeStep 4
Launch JupyterLab
Run this from the folder where you saved the notebook, or move the notebook into the folder Jupyter opens.
jupyter labOpening and running the notebook
Download readiness-arcade.ipynb, move it into the folder where you launched JupyterLab,
then open it from the Jupyter file browser. Run cells with Shift + Enter.
When state feels confusing, use Kernel → Restart Kernel and Run All Cells.
Video walkthrough
Start with the short orientation video
Use the video for the quick tour, then open the slide map and run the notebook diagnostic to decide which stations deserve your time.
Slide navigation
The slides are in 2D
The slides have both horizontal <i>and</i> vertical navigation. Think of left/right as the main arcade path, and up/down as moving through the current arcade.
→←
Main route
Move forward or backward through the main horizontal path.
↓↑
Vertical branches
Move deeper into the details along each topic/arcade.
EscO
Overview
Zoom out to see the two-dimensional map and jump to a section.
SpaceN
Next slide
Advance through the deck.
F?
Other
Use full-screen mode or show the Reveal.js keyboard shortcut help.
The deck
The slides are below and at the link.
Notebook workflow
Use the diagnostic first, then choose your arcades
The notebook is not meant to be completed in one sitting. It is like a gym: do the diagnostic, find the skill that needs work, practice that station, then move on.
Run the start-screen diagnostic
Use this section to decide where to spend your time.
Pick one or two arcades
Start with the station that blocks you the most.
Run, edit, and explain
Use Shift + Enter to run cells, change small values, and write short explanations in your own words.
Try the final boss
When the core habits feel good, try this threshold.