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Home Other Tutorials

Udemy – ChatGPT & Brain-Computer Interfaces: Vibe Coding for all

August 23, 2025
in Other Tutorials, Ai Courses, Free Course, Tutorials
ChatGPT & Brain-Computer Interfaces: Vibe Coding for all
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
Product Details
  • 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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