Name: Mastering Brain-Computer Interfaces & Neurotechnology
Availability: InStock

What You'll Learn

Understand how the human brain generates neural signals and how BCIs interpret them.
Record, filter, and process EEG data to extract meaningful neural features.
Build real BCI pipelines using signal processing, machine learning, and real-time tools.
Develop hands-on applications like neurofeedback, device control, and mental-state decoding.
Use industry frameworks such as OpenBCI, BrainFlow, MNE, and LSL for BCI development.
Evaluate neuroethical, privacy, and security risks and design responsible neurotech systems.

Requirements

No prior neuroscience or neurotechnology experience required.
Basic familiarity with computers and installing software is helpful.
Optional but useful: beginner-level Python programming knowledge.
Access to a Windows, macOS, or Linux computer for running tools.
An EEG headset (OpenBCI, Muse, Emotiv, etc.) is recommended but not required—simulated data is provided.
Curiosity about the brain, AI, and emerging technologies is the most important requirement.

Beginners curious about how brains and computers interact and want a structured introduction.
Students and professionals interested in neuroscience, AI, biomedical engineering, or cognitive science.
Developers, data scientists, and ML engineers wanting to apply their skills to neurotechnology.
Innovators and entrepreneurs exploring brain-tech, wearable tech, or human-AI integration ideas.
Researchers and practitioners seeking hands-on BCI experience with real tools and datasets.
Anyone looking to build neurofeedback systems, mind-controlled apps, or next-generation neurotech products.

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