15 Best Neural Network Courses (Bestseller & Free)

Looking for the best Neural Network courses in 2025? You’re in the right place. Below is a hand-picked list of 15 high-quality courses covering fundamentals to advanced topics-PyTorch, TensorFlow, CNNs, RNNs, transformers, and more. I’ve also added useful reads from KNCMAP after each pick so you can reinforce concepts with our own tutorials.

New to neural nets? Start with these primers from KNCMAP:
• Introduction to Artificial Neural Networks (ANNs)
• Machine Learning 101: A Beginner’s Guide
• Types of Machine Learning: A Comprehensive Guide
• Understanding Tensors: A Comprehensive Guide

Best Neural Network Courses (2025)

Neural Networks and Deep Learning (deeplearning.ai / Coursera)

A classic beginner-friendly intro by Andrew Ng’s team. Covers the building blocks of neural nets, forward/backprop, and practical tips.

Pair with KNCMAP: ANNs: A Comprehensive Guide
Deep Learning Nanodegree (Udacity)

Project-based path covering CNNs, RNNs, GANs, and deployment best practices.

Pair with KNCMAP: List of Image CNN Models · CNN in Python (step-by-step)
Deep Learning A–Z™: Hands‑On Artificial Neural Networks (Udemy)

Wide survey with practical labs: ANN, CNN, RNN, SOMs, Autoencoders.

Pair with KNCMAP: AI vs ML vs Neural Networks
Intro to Deep Learning with PyTorch (Udacity — FREE)

Hands-on PyTorch basics, CNNs, RNNs, and sentiment analysis.

Pair with KNCMAP: Understanding Tensors
Introduction to Deep Learning & Neural Networks with Keras (IBM / Coursera)

Beginner course focusing on Keras fundamentals and model building.

Pair with KNCMAP: ML 101
Deep Neural Networks with PyTorch (IBM / Coursera)

Pytorch-first path: tensors, autograd, CNNs, transfer learning, regularization.

Pair with KNCMAP: CNN with Python (TensorFlow) · Popular CNN Architectures
Intro to TensorFlow for Deep Learning (Udacity — FREE)

TensorFlow 2 workflow, image models, transfer learning, time series, TF Lite.

Pair with KNCMAP: CNNs & Image Processing
Introduction to Deep Learning (edX)

Conceptual course covering core architectures and responsible AI considerations.

Pair with KNCMAP: Types of Machine Learning
Deep Learning in Python (DataCamp — Skill Track)

Sequence of short courses: Keras, TensorFlow, PyTorch, and CNNs with exercises.

Pair with KNCMAP: ML 101
Deep Learning: Convolutional Neural Networks in Python (Udemy)

Focused dive into CNNs for image tasks, embeddings, and TensorFlow 2 workflows.

Pair with KNCMAP: CNNs & Image Processing
Convolutional Neural Networks (deeplearning.ai / Coursera)

Andrew Ng’s CNN course: conv/pooling layers, object detection, style transfer.

Pair with KNCMAP: CNN Architectures Guide
Complete Guide to TensorFlow for Deep Learning with Python (Udemy)

TensorFlow end‑to‑end: ANN, CNN, RNN, Autoencoders, and RL basics.

Pair with KNCMAP (PDFs): ML Libraries & Activation Functions (PDF)
Deep Learning with Python and PyTorch (IBM / edX)

PyTorch training on CNNs, optimizers, initialization, batch norm, and GPUs.

Pair with KNCMAP: Tensors Guide
Introduction to Deep Learning (HSE University / Coursera)

Mathematical and practical introduction, including an image captioning project.

Pair with KNCMAP: AI vs ML vs NN (Explainer)
Introduction to Deep Learning with PyTorch (DataCamp)

Short, beginner-friendly PyTorch course culminating in MNIST and CNN basics.

Pair with KNCMAP: Build a CNN step-by-step