ChatGPT & Brain-Computer Interfaces: Vibe Coding for all

About this course

Lecture 1: Introduction

Introduction to the course. Why do we need it? Why Large Language Model and ChatGPT? Limitations of standart machine learning implementation and prospects for Large Language Model models? Lecture 2: Hardware for Brain-Computer Interface

Introduction to Hardware. How to measure EEG, Difference between real-time and non-real-time applications, etc Lecture 3: Dataset for the CourseWhere to find a dataset for EEG research. How to choose a dataset, etc. Introduction to the dataset. Lecture 4: Machine Learning with Vibe Coding to detect emotions via EEG

How to create a machine learning model via Vibe coding to detect the Emotional stage via EEG signals Lecture 5: EEG detects emotions via OpenAIConnect OpenAI and start making feature extraction from EEG data directly in ChatGPT Lecture 6: Signal Processing and Feature Extraction with OpenAICreate signal processing via vibe coding and continue to make feature extraction via OpenAI Lecture 7. Brain-computer interface connects to OpenAI to make feature extraction from EEGConnect the ironbci Brain-computer interface to OpenAI. Send data from BCI directly to OpenAI for feature extraction Lecture 8. How to improve the Result. Conclusion

How can we improve accuracy, future steps, and prospect direction for Large Language Model and EEG

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