Master BCI & AI
from first principles
Structured video courses on brain-computer interfaces, deep learning, signal processing, and the mathematics behind modern neurotechnology.
12+
Courses planned
4
Topics covered
6+
Expert instructors
1+
Free at launch
BCILattice Quickstart
Set up your first EEG pipeline end-to-end using the BCILattice desktop app.
by BCINexus Team
EEG Fundamentals for Researchers
From electrode placement to artifact rejection, everything you need before touching ML.
by Dr. Sara Yildiz
Motor Imagery BCI Systems
Design, record, and classify motor imagery paradigms with NeuralFlow.
by Dr. James Harlow
P300 & SSVEP Paradigm Design
Build clinical-grade speller and steady-state paradigms with real-time feedback loops.
by Prof. Lin Wei
Deep Learning for Brain Signals
Apply CNNs, LSTMs, and attention mechanisms directly to raw EEG time-series.
by Dr. Aiko Tanaka
Transformers & Vision Transformers for EEG
Leverage self-attention and patch-based encoders for high-accuracy BCI classifiers.
by Dr. Aiko Tanaka
Reinforcement Learning in BCI
Train adaptive decoders that improve in real-time using human neural feedback.
by Dr. Marcus Reid
Linear Algebra for Machine Learning
Vectors, matrices, eigendecomposition, and SVD, the math that powers every BCI model.
by Prof. Elena Mora
Statistics & Probability for Neuroscience
Hypothesis testing, Bayesian inference, and permutation tests for neural data.
by Prof. Elena Mora
Fourier Analysis & Spectral Methods
DFT, STFT, wavelets, and power spectral density, frequency-domain mastery.
by Dr. Omar Al-Rashid
Digital Signal Processing Fundamentals
Filtering, convolution, sampling theory, and IIR/FIR design for biomedical signals.
by Dr. Omar Al-Rashid
Advanced Feature Extraction from EEG
Band power, CSP, connectivity metrics, and entropy features for high-performance classifiers.
by Dr. Sara Yildiz
Don't know where to start?
Follow a curated sequence built for your goal, from zero background to shipping a real BCI application.
BCI Researcher
~34h total
- 1EEG Fundamentals
- 2DSP Fundamentals
- 3Motor Imagery BCI
- 4Advanced Feature Extraction
ML Engineer for Neuro
~36h total
- 1Linear Algebra for ML
- 2Fourier & Spectral Methods
- 3Deep Learning for Brain Signals
- 4Transformers for EEG
BCILattice Power User
~30h total
- 1BCILattice Quickstart
- 2EEG Fundamentals
- 3Motor Imagery BCI
- 4P300 & SSVEP Paradigms
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