Udemy

EEG/ERP Analysis with Python and MNE: An Introductory Course

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  • 1,192 名學生
  • 更新於 10/2025
4.4
(199 個評分)
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課程資料

報名日期
全年招生
課程級別
學習模式
修業期
7 小時 52 分鐘
教學語言
英語
授課導師
Neura Skills, Neura Skills Team
評分
4.4
(199 個評分)

課程簡介

EEG/ERP Analysis with Python and MNE: An Introductory Course

From Brain Signal Basics to Advanced Analysis

Whether you're a novice in the field or looking to enhance your skills, this course is your gateway to understanding the basics of EEG data analysis.

A Journey Through EEG History: Join us on a fascinating exploration of the origins of EEG data, from its introduction to the cutting-edge techniques used today.

Recording EEG Data: Learn the essentials of recording high-quality EEG data and what constitutes good EEG data. Learn the basics of artifacting, recognizing different types of noises, and witness noise reduction in action through various filtering techniques.

Frequency and Time Domain Analyses: Demystify the complexities of frequency and time domain analyses. Understand different brain frequencies, conduct frequency analysis, explore time domain analysis and Event-Related Potentials (ERPs), and venture into time-frequency analysis.

Python for EEG Analysis: Familiarize yourself with Python basics, ANACONDA installation, coding fundamentals, and data plotting. Install MNE (MNE-Python) and kickstart your journey into EEG analysis.

MNE-Python Pre-processing: Explore MNE-Python for pre-processing EEG data. Import data, gain an overview, implement filtering, reject bad channels, and perform Independent Component Analysis (ICA) for noise removal.

Frequency Analysis with Python and MNE: Utilize MNE's PSD function for frequency analysis. Create visually stunning frequency band plots and topographic maps to explore the mysteries hidden within EEG data.

Exploring Important ERPs: Review essential Event-Related Potentials (ERPs), such as the P300 and N170 components, along with language-related components. Understand their significance and applications in EEG analysis.

ERP and Time-Frequency Analysis in Python and MNE: Master the art of visualizing ERPs using Python. Leverage MNE for interpreting ERPs and delve into plotting and interpreting time-frequency analyses.

Why Choose This Course:

This course is designed for beginners, providing a seamless transition from the basics to advanced EEG analysis techniques. With hands-on Python coding exercises and practical examples using MNE-Python, you'll gain practical skills that are essential for anyone seeking proficiency in EEG data analysis.

Join us on this educational journey, and let's unravel the mysteries of EEG together! Enroll now to kickstart your EEG analysis adventure.

課程章節

  • 10 個章節
  • 46 堂課
  • 第 1 章 Introduction to EEG
  • 第 2 章 Frequency and time domain analyses
  • 第 3 章 The essence of artifacting
  • 第 4 章 Start working with Python
  • 第 5 章 Pre-processing with MNE-Python
  • 第 6 章 Frequency analysis in Python and MNE
  • 第 7 章 Review of important ERPs
  • 第 8 章 ERP and time-frequency analysis in Python and MNE
  • 第 9 章 Extra+Advance with ChatGPT
  • 第 10 章 Course Materials

課程內容

  • Understanding the Basics of Electrophysiology Data
  • Start Working with Python
  • Gain Expertise in Frequency Domain Analysis of Electrophysiological Data
  • Learn to Identify and Analyze ERPs
  • Acquire the Practical Skills to Conduct Time-Frequency Analysis using Python and the MNE library.


評價

  • A
    Anagha P B
    5.0

    The course is really good for someone who is an amateur in EEG. The instructor did not leave any part unexplained. It would have been nice if subtitles were provided for the videos. Thanks for the course!!

  • T
    TARIQ Oqielat
    5.0

    good job

  • P
    Putta Revanth
    4.5

    good

  • J
    Jin Li Lim
    5.0

    Concise description and hands-on learning of python

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