Published 3/2026
Created by Neura Skills, Neura Skills Team
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 31 Lectures ( 6h 9m ) | Size: 3.51 GB
Sleep EEG and Python
What you’ll learn
✓ Understand different brain waves during sleep (slow waves, spindles, K-complexes) and what they mean
✓ Learn how to visualize, and explore sleep EEG data using Python (MNE & YASA)
✓ Perform sleep staging and understand how sleep scoring works (manual and automatic)
✓ Detect sleep events such as slow oscillations and sleep spindles from real data
Requirements
● No advanced programming experience needed
Description
Sleep EEG can feel overwhelming at first, we have long recordings, complex signals, and unfamiliar patterns. But once you learn how to read it, EEG becomes a powerful tool to understand the sleeping brain. This course is not just about coding. It is also about understanding what the brain waves mean during sleep. The code is kept simple and clear, so you can learn without feeling overwhelmed. In this course, you will learn how to go from raw EEG data to meaningful results using Python. You will start with the basics of sleep and EEG. You’ll learn how to recognize sleep stages and important features like slow waves, sleep spindles, and K-complexes. Then, you’ll work with real EEG data using MNE and YASA. Next, you will learn practical analysis skills. You will also learn how to automatically detect sleep events and extract useful features. By the end of this course, you will be able to
Load and explore full-night EEG recordings
Perform sleep staging (manual and automatic)
Detect slow waves and spindles
Analyze data in time and frequency
Extract features for research
This course is designed for students, researchers, and professionals in neuroscience, psychology, biomedical engineering, and data science.
No advanced coding is needed. Everything is explained step by step. By the end, you won’t just see EEG signals, you will understand and analyze them with confidence. Let’s start our sleep exploration.
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