Start Building Artificial Neural Networks in Python

Even if you know absolutely nada about neural networks, by the end of the course you’ll be building your own ANNs and fully understanding how they work.

It’s not always easy to get started with neural networks. There’s either too much math or not enough under-the-hood explanation for each project.

With us, you’ll get the best of both worlds:

You’ll get just enough of the underlying math to understand how ANNs work. We walk you through the mathematical concepts behind a neural network, step by step. Even if you come to the course knowing nothing about neural networks, you will still be able to follow our guided walkthroughs.

You’ll find it super easy to learn. Our students want to act on what they’ve studied. In Neural Networks in Python, you’ll build and implement an ANN from the ground up. By the end of the course, you’ll have understood each step in the process of building an artificial neural network.

Neural Networks in Python gives you all the tools for building and deploying a powerful computing system within hours.

For a newbie, an ANN’s versatility can also be their greatest drawback. How can we know we have chosen the right model for our project? Which learning algorithm and cost function should we select?

Whether you’re a complete beginner or an undergraduate studying a subject related to AI, Neural Networks in Python will show you exactly how to build and deploy ANNs for your projects.

Yes, beginners are welcome!

Taking your first steps? Neural Networks in Python gives you all you need to get started. AI expert and instructor Jones Granatyr explains each phase to building and deploying an ANN.

Already know your way around neural networks? This course will help you to revise and review all the critical terminology associated with ANNs, all in one helpful online space.