2025 Brain-Computer Interface: AI Integration Course

2025 Brain Computer Interface with AI

Brain Computer Interface | Artificial Intelligence | Machine Learning | Python

Created by : Rated :4.3 2231 views

Last Updated: 2025-01-23 10:01:35 English Course Type: Self Learning

you will learn what is BCI
you will understand EEG signal
you will learn how to deep neural networks
you will learn how to do feature extraction
you will learn how to build a system to classify your thoughts using deep Neural Networks
you will learn how to extract the images in your brain using deep Neural Networks

Dive into the amazing world of Brain-Computer Interfaces (BCI) with our course, "Mind Meets Machine: Exploring Brain-Computer Interfaces (BCI)" . Discover how BCIs have evolved from early experiments in the 1950s to the groundbreaking technologies of today .

In this course, you will learn about EEG signals , the electrical waves our brains produce. You'll understand how to use deep neural networks, the powerful tools behind modern AI , and how to extract important features from brain data . We will delve into the complexities of these signals and how they can be harnessed to bridge the gap between mind and machine.

We'll guide you step-by-step on how to build a sophisticated system that can classify your thoughts using deep neural networks . Imagine being able to extract and visualize the very images formed in your brain—this course makes that possible! With hands-on projects and real-world examples, you’ll gain practical experience in developing BCI applications.

Our easy-to-follow lessons combine theory with practical exercises, ensuring you can apply what you learn effectively . By the end of this course, you'll have the skills to create exciting BCI applications, connecting the human mind with technology in new and exciting ways . Join us and be part of the future of neuroscience and AI! Embrace this opportunity to be at the forefront of innovation, and transform your understanding of the brain’s potential.

Deep Learning Basics
Curiosity and Creativity
Python Basics

Students
Curious Learners
Professionals Seeking New Skills

Section 1 : BCI Introduction 3 Lectures 00:04:35
Lecture 1 :
What is BCI ? Preview
Lecture 2 :
What is EEG signal ?
Lecture 3 :
How to Create Notebooks in Google Colab ?
Section 2 : Deep Learning 8 Lectures 00:36:58
Lecture 1 :
What is Deep Learning ?
Lecture 2 :
What is MNIST dataset ?
Lecture 3 :
loading MNIST dataset python code
Lecture 4 :
Data Preprocessing python code
Lecture 5 :
How to create a simple neural network ?
Lecture 6 :
Building simple neural network python code
Lecture 7 :
How to train your Neural Network ?
Lecture 8 :
Training your Network python code
Section 3 : Project 1 12 Lectures 00:55:37
Lecture 1 :
What We Will Do in Our Project ?
Lecture 2 :
Loading The Data python code
Lecture 3 :
Data Segmentation
Lecture 4 :
How to Divide Data into Training and Testing Sets ? python code
Lecture 5 :
Data Preprocessing python code
Lecture 6 :
How to build a CNN network ? python code
Lecture 7 :
Training and Testing part1
Lecture 8 :
let's do segmentation python code part 1
Lecture 9 :
let's do segmentation python code part 2
Lecture 10 :
Training and Testing part2
Lecture 11 :
Training and Testing part3
Lecture 12 :
How to build a CNN network ?
Section 4 : Project 2 16 Lectures 01:24:02
Lecture 1 :
What is the objective ?
Lecture 2 :
Data Preprocessing
Lecture 3 :
Data Preprocessing python code
Lecture 4 :
Building a CNN network For Feature Extraction
Lecture 5 :
What is Gan network and how it works ?
Lecture 6 :
Building Discriminator network python code part 1
Lecture 7 :
Training and Testing GAN Network part1
Lecture 8 :
Training and Testing GAN Network part2
Lecture 9 :
Training and Testing GAN Network part3
Lecture 10 :
Training and Testing GAN Network part4
Lecture 11 :
Building Generator network python code part2
Lecture 12 :
Building Discriminator network python code part 2
Lecture 13 :
Building a CNN network For Feature Extraction python code part1
Lecture 14 :
Building a CNN network For Feature Extraction python code part2
Lecture 15 :
Building Generator network python code part 1
Lecture 16 :
Building Generator network python code part3

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Riad Neema,

2231 Course Views

1 Courses

My name is Riad, and I’ve been passionate about artificial intelligence and machine learning for over five years. Through dedication and hands-on experience, I have become one of the leading experts in machine learning, deep learning, and reinforcement learning on Kaggle.

I’ve participated in two prestigious AI competitions on Kaggle, earning silver medals in both. The first was the MOA competition, followed by the Pet Finder competition, where I leveraged my expertise to develop cutting-edge solutions and achieved recognition.