Neural Networks Courses and Certifications

Introduction to Neural Networks

10 ratings at Coursera

Learn the mathematics behind neural networks: train models with gradient descent, build deep feedforward architectures, apply dropout and regularization, and explore convolutional networks for computer vision.

• Coursera
• 5 weeks, 4 hours a week
• Self-Paced
• Paid Course

Mastering Neural Networks and Model Regularization

Build neural networks from scratch and in PyTorch: perceptrons, back-propagation, L1/L2 and dropout regularization, and CNNs for MNIST images and audio spectrograms.

• Coursera
• 5 weeks, 3 hours a week
• Self-Paced
• Paid Course

The Complete Neural Networks Bootcamp: Theory, Applications

3091 ratings at Udemy

Deep Learning and Neural Networks Theory and Applications with PyTorch! Including Transformers, BERT and GPT!

• Udemy
• 1 day 19 hours 47 minutes
• Self-Paced
• Paid Course

Neural Networks in Python: Deep Learning for Beginners

1920 ratings at Udemy

Learn Artificial Neural Networks (ANN) in Python. Build predictive deep learning models using Keras & Tensorflow| Python

• Udemy
• 9 hours 21 minutes
• Self-Paced
• Paid Course

Neural Networks and Random Forests

18 ratings at Coursera

Build neural networks in Python with TensorFlow and Keras, handle overfitting and regularization, then compare decision trees and random forests on health and species prediction projects.

• Coursera
• 4 weeks, 3 hours a week
• Self-Paced
• Paid Course

Machine Learning with Neural Networks

Learn to build neural networks: feed-forward functions, gradient-based training with backpropagation, regularization for generalization, and Bayesian networks that quantify uncertainty, implemented in TensorFlow.

• Coursera
• 7 weeks, 5 hours a week
• Self-Paced
• Paid Course

Edureka

Neural Networks and Computer Vision Foundations

Build neural networks from scratch: implement forward passes and backpropagation, tune optimizers and regularization, then train CNNs for image classification, detection, and segmentation.

• Coursera
• 4 weeks, 3 hours a week
• Self-Paced
• Paid Course

Coursera

Start Neural Networks Advanced Model Architectures

Build feed-forward neural networks in Keras/PyTorch, diagnose overfitting through learning-curve analysis, and apply dropout and L2 regularization to hit generalization targets.

• Coursera
• 2 weeks, 1 hour a week
• Self-Paced
• Paid Course

EDUCBA

Apply Neural Networks for Car Price Prediction

Build a neural network regression model to predict car prices: explore structured data, encode and scale features, evaluate with mean squared error, and apply regularization.

• Coursera
• 2 weeks, 3 hours a week
• Self-Paced
• Paid Course

Convolutional Neural Networks

8 ratings

Build convolutional neural networks and residual variants, apply transfer learning, and implement object detection, face recognition, and neural style transfer for art generation.

• Coursera
• 4 weeks, 9 hours a week
• Self-Paced
• Paid Course

Neural Networks Demystified

In this short series, we will build and train a complete Artificial Neural Network in python.

• YouTube
• 30 minutes
• Self-Paced
• Free Video

Neural Networks from Scratch in Python

Implement a feedforward neural network from scratch in Python, covering neurons, layers, dot products, activation functions, softmax, and categorical cross-entropy.

• YouTube
• 3 hours 30 minutes
• Self-Paced
• Free Video

3Blue1Brown

Neural Networks and Deep Learning Fundamentals

Discover neural networks fundamentals and backpropagation through visual explanations, plus explore transformers and LLMs that power modern AI applications.

• YouTube
• 3 hours 4 minutes
• Self-Paced
• Free Video

Coding Train

Neural Networks - The Nature of Code

Dive into neural networks from perceptrons to backpropagation with hands-on coding examples, matrix math, and practical projects like doodle classification.

• YouTube
• 8 hours 48 minutes
• Self-Paced
• Free Video

Artificial Intelligence

239 ratings

This course introduces students to the basic knowledge representation, problem solving, and learning methods of artificial intelligence.

• MIT OpenCourseWare
• 24 hours
• Self-Paced
• Free Video