Free Course

Intro to TensorFlow for Deep Learning

by
TensorFlow

This course is a practical approach to deep learning for software developers

Nanodegree Program

Deep Learning

Build cutting-edge AI projects supported by dedicated mentors.

About this Course

Learn how to build deep learning applications with TensorFlow. This course was developed by the TensorFlow team and Udacity as a practical approach to deep learning for software developers. You'll get hands-on experience building your own state-of-the-art image classifiers and other deep learning models. You'll also use your TensorFlow models in the real world on mobile devices, in the cloud, and in browsers. Finally, you'll use advanced techniques and algorithms to work with large datasets. By the end of this course, you'll have all the skills necessary to start creating your own AI applications.

We are releasing a first batch of lessons and more will become available every 3-4 weeks.

Course Cost
Free
Timeline
Approx. 2 month
Skill Level
intermediate
Included in Product

Rich Learning Content

Taught by Industry Pros

Interactive Quizzes

Self-Paced Learning

Join the Path to Greatness

This course is your first step towards a career in Deep Learning.

Free Course

Intro to TensorFlow for Deep Learning

byTensorFlow

Learn how to build deep learning applications with TensorFlow.

Icon steps
 
 

Course Leads

Magnus Hyttsten

Magnus Hyttsten

Developer Advocate, Google

Juan Delgado

Juan Delgado

Content Developer, Udacity

Paige Bailey

Paige Bailey

Developer Advocate, Google

What You Will Learn

lesson 1

What is Artificial Intelligence and Machine Learning?

  • Get a high-level overview of artificial intelligence and machine learning
  • Learn how machine learning and deep learning have revolutionized software
lesson 2

Your first model: Fashion MNIST

  • Build a neural network that can recognize images of articles of clothing
lesson 3

More efficient image classification

  • Use a convolutional network to build more efficient models for Fashion MNIST
lesson 4

Turn a binary classifier into a multi-class classifier

  • Expand your image classifiers into models that can predict from multiple classes
  • Use a convolutional network to build a classifier for more detailed color images
lesson 5

Transfer Learning

  • Use a pre-trained network to build powerful state-of-the-art classifiers
lesson 6

Saving and Loading Models

  • Look at the new SAVEDMODEL format in TensorFlow 2.0 and take advantage of it for TensorFlow-Lite and TensorFlow-Serving
lesson 7

Machine Learning on devices with TensorFlow Lite

  • Learn how you can use TensorFlow Lite to build machine learning apps on Android, iOS and iOT devices
lesson 8

Machine Learning in the Cloud with TensorFlow-Serving

  • Use TensorFlow-Serving to deploy a machine learning model to the cloud
lesson 9

Machine Learning in-the-browser with TensorFlow.js

  • Use TensorFlow.js to train models and make predictions all in a browser
lesson 10

Machine Learning-based products and services from Google

  • Learn about MLKit, ML services on Google Cloud Platform, and put your models on these infrastructures
lesson 11

The Workflow of Machine Learning

  • Learn about the workflow of Machine Learning and the steps that lead to success
  • Learn how to get data, define the problem, understand success, and build and evaluate models
lesson 12

Managing Data

  • Learn about data structures in TensorFlow, including tensors and how to manipulate them
  • Learn how to get data into TensorFlow from common sources, from CSV to BigQuery
lesson 13

Exploring Neural Nets in Keras

  • Dive deep into the inner workings of TensorFlow to learn about tensor operations, gradient-based optimization, and graphs
  • Use the Keras layers API to build complex neural networks
lesson 14

Going deeper into Neural Nets

  • Learning from sequential data with recurrent neural networks
  • Unsupervised learning with generative adversarial networks

Prerequisites and Requirements

To get the most out of your experience, we recommend the following:

  • Beginning Python syntax, including: variables, functions, classes, and object-oriented programming
  • Basic algebra

See the Technology Requirements for using Udacity.

Why Take This Course

Learn how to build deep learning applications with TensorFlow. You'll get hands-on experience building your own state-of-the-art image classifiers and other deep learning models. You'll also use your TensorFlow models in the real world on mobile devices, in the cloud, and in browsers. By the end of this course, you'll have all the skills necessary to start creating your own AI applications.

What do I get?
Instructor videosLearn by doing exercisesTaught by industry professionals