🧠 An EEG Analysis x Python Journey
"The brain isn't a computer. It's a chaotic pile of electric meat trying its best to translate reality into a language we can understand"
This is not a passive course. Every day, you get your hands dirty — loading real EEG data, debugging real code, and building real intuition. We start with Python fundamentals and end with publication-grade statistics. No shortcuts, no magic boxes. Just you, the signal, and a terminal.
Hover over any card to reveal what you'll actually be doing that day
Becoming a brain-data ninja. Tame your arrays before they tame you.
↗️Turning arrays of raw numbers into a visual story, because your eyes are better at spotting patterns (mistakes).
↗️Flattening the curve of your dimension confusion. DataFrames are great — until they aren't.
↗️Throwing out the bad apples before making neural cider. Garbage in, garbage out.
↗️Artifact Subspace Reconstruction — politely asking the noise to leave the room. Goodbye, muscle artifacts.
↗️Independent Component Analysis — separating your actual brainwaves from your excessive blinking, heartbeats, and muscle smirks.
↗️Letting an algorithm judge your brain's noisy habits. Auto-classify ICA components with confidence.
↗️Stripping away the drama to find the main characters of your data. Welcome to the eigenvalue era.
↗️Figuring out exactly where your brain's energy bill is going. Alpha, beta, gamma — who's freeloading?
↗️Catching those brain waves while they're on the move. Instantaneous frequency — not as instant as coffee, but close.
↗️Fitting Oscillations & One Over F — because sometimes the "background noise" is the real story.
↗️Un-fractaling your thoughts to see what's actually oscillating. Separate the rhythmic from the chaotic.
↗️Measuring exactly how long your brain holds onto a grudge… or a signal. Temporal persistence quantified.
↗️For when you absolutely need to know exactly when and what happened. Time-frequency precision.
↗️Smoothing things over when your spectrum is looking a little too jagged. Multiple tapers, multiple peace of mind.
↗️Adding an imaginary friend to your very real data. The holy trinity of signal: envelope, phase, frequency.
↗️Finding out if brain regions are actually talking, or just gossiping. True synchrony vs. volume conduction.
↗️Shuffling the deck until your p-value finally cries uncle. Non-parametric, assumption-free inference.
↗️Because one significant pixel is a fluke, but a blob is a discovery. Spatial-temporal cluster correction.
↗️Threshold-Free Cluster Enhancement — because setting arbitrary cutoffs is so last century. The final boss.
↗️Cognitive Scientist · EEG Analyst · Open-Science Advocate
We as a team have spent years decoding the brain's electrical whispers and translating them into actionable science. This course is a distillation of everything we wished had been taught in a single, coherent, hands-on sequence so you can skip the decade of stumbling and go straight to the good stuff.