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TensorFlow - Data and Deployment Coursera

Highlights
Tuition fee
Free
Free
Unknown
Tuition fee
Free
Free
Unknown
Duration
1 months
Duration
1 months
Apply date
Anytime
Unknown
Apply date
Anytime
Unknown
Start date
Anytime
Unknown
Start date
Anytime
Unknown
Taught in
English
Taught in
English

About

In this TensorFlow - Data and Deployment Specialization offered by Coursera in partnership with Deeplearning, you’ll learn how to get your machine learning models into the hands of real people on all kinds of devices.  The TensorFlow - Data and Deployment Specialization is offered by Coursera in partnership with Deeplearning.

Overview

Continue developing your skills in TensorFlow as you learn to navigate through a wide range of deployment scenarios and discover new ways to use data more effectively when training your machine learning models.

Start by understanding how to train and run machine learning models in browsers and in mobile applications. Learn how to leverage built-in datasets with just a few lines of code, learn about data pipelines with TensorFlow data services, use APIs to control data splitting, process all types of unstructured data, and retrain deployed models with user data while maintaining data privacy.  Apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more. 

Industries all around the world are adopting Artificial Intelligence. This Specialization from Laurence Moroney and Andrew Ng will help you develop and deploy machine learning models across any device or platform faster and more accurately than ever.

Applied Learning Project

In the TensorFlow - Data and Deployment Specialization offered by Coursera in partnership with Deeplearning, you will learn to apply your knowledge in various deployment scenarios and get introduced to TensorFlow Serving, TensorFlow, Hub, TensorBoard, and more, implementing projects you can add to your portfolio and show in interviews. 

Programme Structure

Courses include:

  • Browser-based Models with TensorFlow.js

  • Device-based Models with TensorFlow Lite

  • Data Pipelines with TensorFlow Data Services

  • Advanced Deployment Scenarios with TensorFlow

Key information

Duration

  • Part-time
    • 1 months
    • 10 hrs/week

Start dates & application deadlines

You can apply for and start this programme anytime.

Language

English

Delivered

Online
  • Self-paced

Campus Location

  • Mountain View, United States

What students do after studying

Join for free or log in to access our complete career info list.

Academic requirements

We are not aware of any specific GRE, GMAT or GPA grading score requirements for this programme.

English requirements

We are not aware of any English requirements for this programme.

Other requirements

General requirements

Intermediate Level

  • Some related experience required.

Tuition Fees

Tuition fees are shown in and the most likely applicable fee is shown based on your nationality.
  • International

    Non-residents
    Free
  • Out-of-State
    Free

Additional Details

  • Audit: free access to course materials except graded items
  • Certificate: a trusted way to showcase your skills
  • A year of unlimited access with Coursera Plus $199

Funding

Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. 

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