Neural Networks Courses and Certifications

Career Certificate

AI Programming with Python

39 ratings

Develop Python skills for AI, covering libraries, linear algebra, calculus, and neural networks. Build an image classifier using PyTorch and explore Transformer models.

• Udacity
• 52 hours
• Self-Paced
• Paid Course

Recurrent Neural Networks (RNNs) for Language Modeling with Keras

Learn how to use RNNs to classify text sentiment, generate sentences, and translate text between languages.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Deep Learning A-Z 2026: Neural Networks, AI & ChatGPT Prize

49373 ratings at Udemy

Learn to create Deep Learning models in Python from two Machine Learning, Data Science experts. Code templates included.

• Udemy
• 22 hours 33 minutes
• Self-Paced
• Paid Course

Advanced Neural Network Techniques

Master advanced neural network architectures including RNNs, Autoencoders, GANs, and Deep Reinforcement Learning through hands-on projects and real-world applications, from mathematical foundations to practical implementation.

• Coursera
• 10 hours 48 minutes
• Self-Paced
• Paid Course

Data Science: Deep Learning and Neural Networks in Python

10276 ratings at Udemy

The MOST in-depth look at neural network theory for machine learning, with both pure Python and Tensorflow code

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

Introduction to Neural Networks with TensorFlow

Master neural networks and deep learning fundamentals using TensorFlow, from data preprocessing to model training. Build and optimize architectures, implement activation functions, and enhance model performance with the Digits dataset.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

JAX in Action: Neural Networks from Scratch

Master neural network fundamentals by building an MLP from scratch using JAX, tackling XOR classification with parameter management, forward propagation, and manual training loops.

• CodeSignal
• 2 hours
• Self-Paced
• Free Certificate

Improving Neural Networks with PyTorch

Master advanced PyTorch techniques like dropout, early stopping, and batch normalization to transform weak neural networks into robust, high-performing models through hands-on implementation.

• CodeSignal
• 1 hour
• Self-Paced
• Free Certificate

Training Neural Networks: the Backpropagation Algorithm

Master the backpropagation algorithm by implementing loss functions, gradient descent, and SGD optimizers to train neural networks using R.

• CodeSignal
• 3 hours
• Self-Paced
• Free Certificate

Convolutional Neural Networks in TensorFlow

8225 ratings at Coursera

Explore advanced ConvNet techniques for image classification, including data augmentation, transfer learning, and multiclass categorization using TensorFlow's high-level APIs.

• Coursera
• 16 hours 17 minutes
• Self-Paced
• Paid Course

Artificial Neural Network for Regression

6431 ratings at Udemy

Build an ANN Regression model to predict the electrical energy output of a Combined Cycle Power Plant

• Udemy
• 1 hour 12 minutes
• Self-Paced
• Free Online Course

NPTEL;  IIT Kharagpur

Data Mining

43 ratings

Comprehensive exploration of data mining techniques, covering preprocessing, association rules, classification methods, and clustering algorithms for extracting valuable insights from datasets.

• YouTube
• 16 hours
• Self-Paced
• Free Video

Introduction to Artificial Neural Network and Deep Learning

1979 ratings at Udemy

The Best Machine Learning Techniques for Data Science in Java and Neuroph with Application in Image Recognition

• Udemy
• 7 hours 3 minutes
• Self-Paced
• Paid Course

Introduction to Deep Learning & Neural Networks with Keras

2126 ratings at Coursera

. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what is deep learning, and how do deep learning models compare to artificial neural networks?

• Coursera
• 10 hours 10 minutes
• Self-Paced
• Paid Course

Introduction to Neural Networks and PyTorch

1910 ratings at Coursera

Learn to build and train deep neural networks using PyTorch, covering tensors, linear regression, logistic regression, CNNs, and transfer learning for practical AI applications.

• Coursera
• 18 hours 4 minutes
• Self-Paced
• Paid Course