File Name: | ChatGPT & Brain-Computer Interfaces: Vibe Coding for all |
Content Source: | https://www.udemy.com/course/chatgpt-brain-computer-interfaces-vibe-coding-for-all |
Genre / Category: | Other Tutorials |
File Size : | 791.4 MB |
Publisher: | Ildar Rakhmatulin |
Updated and Published: | August 23, 2025 |
- 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 Course: Where 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 OpenAI: Connect OpenAI and start making feature extraction from EEG data directly in ChatGPT
- Lecture 6: Signal Processing and Feature Extraction with OpenAI: Create 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 EEG: Connect 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
Who this course is for:
- Individuals with a strong interest in EEG and brain-computer interfaces who want to explore the technical aspects of EEG signal processing as a hobby or personal project.
- Graduate and advanced undergraduate students in fields such as neuroscience, biomedical engineering, data science, and psychology, as well as educators looking to integrate EEG signal processing into their curriculum.
- Neuroscientists and Researchers: Professionals and academics who want to leverage Python for analyzing EEG data to advance their research in neuroscience and related fields.
- For neuro enthusiasts
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