TensorFlow: From Basics to Mastery

If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This Specialization will teach you best practices for using TensorFlow, a popular open-source framework for machine learning. In these courses you will:

  • Learn how to build machine learning models in TensorFlow
  • Build image recognition algorithms with deep neural networks and convolutional neural networks
  • Understand how to deploy your models on mobile and the web
  • Go beyond image recognition into object detection, text recognition, and more
  • Expand the basic APIs for custom learning/training

The Machine Learning course and Deep Learning Specialization teach the most important and foundational principles of Machine Learning and Deep Learning. This new deeplearning.ai TensorFlow Specialization teaches you how to use TensorFlow to implement those principles so that you can start building and applying scalable models to real-world problems. To develop a deeper understanding of how neural networks work, we recommend that you take the Deep Learning Specialization. The full deeplearning.ai TensorFlow Specialization will be available later this year, but you can get started with Course 1, Introduction to Tensorflow for AI, ML and DL, available now on Coursera.

Course 1: Introduction to TensorFlow for AI, ML and DL

This first course introduces you to TensorFlow, a popular machine learning framework. You will learn how to build a basic neural network for computer vision and use convolutions to improve your neural network.

Week 1: A New Programming Paradigm

  • Introduction: A conversation with Andrew Ng
  • A primer in machine learning
  • The “Hello World” of neural networks
  • Working through “Hello World” in TensorFlow and Python

Week 2: Introduction to Computer Vision

  • A conversation with Andrew Ng
  • An introduction to computer vision
  • Writing code to load training data
  • Coding a computer vision neural network
  • Walk through a notebook for computer vision
  • Using callbacks to control training
  • Walk through a notebook with callbacks

Week 3: Enhancing Vision with Convolutional Neural Networks

  • A conversation with Andrew Ng
  • What are convolutions and pooling?
  • Implementing convolutional layers
  • Implementing pooling layers
  • Improving the fashion classifier with convolutions
  • Walking through convolutions

Week 4: Using Real-World Images

  • A conversation with Andrew Ng
  • Understanding ImageGenerator
  • Defining a ConvNet to use complex images
  • Training the ConvNet with fit_generator
  • Walking through developing a ConvNet
  • Walking through training the ConvNet with fit_generator
  • Adding automatic validation to test accuracy
  • Exploring the impact of compressing images
  • Outro: Conversation with Andrew

Frequently Asked Questions

Who is the deeplearning.ai TensorFlow Specialization for?
The deeplearning.ai TensorFlow Specialization is for anyone who has basic experience coding in Python and wants to learn how to best use TensorFlow to start building AI applications.
What will I learn in Course 1?
You will learn how to build a basic neural network for computer vision within TensorFlow, as well as how to use convolutions to improve your neural network.
Are there any prerequisites?
You should be comfortable coding in Python and understand high school-level math. Prior machine learning or deep learning knowledge is helpful but not required.
How do I take Course 1?
You can enroll in the course on Coursera’s platform. You will watch videos and complete assignments on Coursera as well.
How long is Course 1?
It typically takes 4 weeks, 4-5 hours per week to complete the first course.
How much does Course 1 cost?
The first course costs $49 for 180 days of certificate eligibility. When the full deeplearning.ai TensorFlow Specialization is available, it will cost $49/month.
Can I apply for financial aid?

Yes, Coursera provides financial aid to learners who cannot afford the fee. You can apply for it by going to the Coursera course page and clicking on the Financial Aid link beneath the “Enroll” button on the left.

Will I receive a certificate at the end of Course 1?
You will receive a certificate at the end of the course if you pay the $49 course price and complete the programming assignments within 180 days. If you audit the course for free, you will not receive a certificate.
Is this a stand-alone course or a Specialization?
You can take Course 1 of the deeplearning.ai TensorFlow Specialization now on Coursera. Future courses will be released over the next several months.

About the Instructors

Laurence Moroney is a Developer Advocate at Google working on Artificial Intelligence with TensorFlow. As the author of more programming books than he can count, he’s excited to be working with deeplearning.ai and Coursera in producing video training.

When not working with technology, he’s a member of the Science Fiction Writers of America, having authored several science fiction novels, a produced screenplay and comic books, including the prequel to the movie ‘Equilibrium’ starring Christian Bale. Laurence is based in Washington State, where he drinks way too much coffee.

Andrew Ng is a global leader in AI and co-founder of Coursera. Dr. Ng is also the CEO and founder of deeplearning.ai and founder of Landing AI. He is an Adjunct Professor in the Computer Science Department at Stanford University.

He was until recently Chief Scientist at Baidu, where he was responsible for driving the company’s global AI strategy and infrastructure. He was also the founding lead of the Google Brain team. Dr. Ng has authored or co-authored over 100 research papers in machine learning, robotics and related fields. He holds degrees from Carnegie Mellon University, MIT and the University of California, Berkeley.

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