Skip to main content
skill track

Deep Learning in Python

In this track, you'll expand your deep learning knowledge and take your machine learning skills to the next level. Working with Keras and PyTorch, you’ll learn about neural networks, the deep learning model workflows, and how to optimize your models. You'll then use TensorFlow to build linear regression models and neural networks. Throughout the track, you'll use machine learning techniques to solve real-world challenges, such as predicting housing prices, building a neural network to predict handwritten numbers, and identify forged banknotes. By the end of the track, you'll be ready to use Keras to train and test complex, multi-output networks and dive deeper into deep learning.

PythonClock16 hoursLearn4 Courses

Create Your Free Account

GoogleLinkedInFacebook

or

By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.

Loved by learners at thousands of companies

1
Python
Introduction to Deep Learning in Python

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0 in Python.

4 hours

Dan Becker Headshot

Dan Becker

Data Scientist and contributor to Keras and TensorFlow libraries

2
Python
Introduction to TensorFlow in Python

Learn the fundamentals of neural networks and how to build deep learning models using TensorFlow.

4 hours

Isaiah Hull Headshot

Isaiah Hull

Economist

3
Python
Introduction to Deep Learning with Keras

Learn to start developing deep learning models with Keras.

4 hours

Miguel Esteban Headshot

Miguel Esteban

Data Scientist & Founder

4
Python
Advanced Deep Learning with Keras

Build multiple-input and multiple-output deep learning models using Keras.

4 hours

Zachary Deane-Mayer Headshot

Zachary Deane-Mayer

VP, Data Science at DataRobot

Track statement of accomplishment

Instructors