About this Specialization
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100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Intermediate Level

Approx. 1 month to complete

Suggested 14 hours/week

English

Subtitles: English, Spanish, Russian

What you will learn

  • Check

    Best practices for TensorFlow, a popular open-source machine learning framework to train a neural network for a computer vision applications.

  • Check

    Handle real-world image data and explore strategies to prevent overfitting, including augmentation and dropout.

  • Check

    Build natural language processing systems using TensorFlow.

  • Check

    Apply RNNs, GRUs, and LSTMs as you train them using text repositories.

Skills you will gain

Computer VisionConvolutional Neural NetworkMachine LearningNatural Language Processing
Learners taking this Specialization are
  • Data Scientists
  • Machine Learning Engineers
  • Chief Technology Officers (CTOs)
  • Data Engineers
  • Biostatisticians

100% online courses

Start instantly and learn at your own schedule.

Flexible Schedule

Set and maintain flexible deadlines.

Intermediate Level

Approx. 1 month to complete

Suggested 14 hours/week

English

Subtitles: English, Spanish, Russian

How the Specialization Works

Take Courses

A Coursera Specialization is a series of courses that helps you master a skill. To begin, enroll in the Specialization directly, or review its courses and choose the one you'd like to start with. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. It’s okay to complete just one course — you can pause your learning or end your subscription at any time. Visit your learner dashboard to track your course enrollments and your progress.

Hands-on Project

Every Specialization includes a hands-on project. You'll need to successfully finish the project(s) to complete the Specialization and earn your certificate. If the Specialization includes a separate course for the hands-on project, you'll need to finish each of the other courses before you can start it.

Earn a Certificate

When you finish every course and complete the hands-on project, you'll earn a Certificate that you can share with prospective employers and your professional network.

how it works

There are 4 Courses in this Specialization

Course1

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

4.7
3,947 ratings
784 reviews
Course2

Convolutional Neural Networks in TensorFlow

4.7
1,565 ratings
215 reviews
Course3

Natural Language Processing in TensorFlow

4.6
1,016 ratings
138 reviews
Course4

Sequences, Time Series and Prediction

4.6
634 ratings
104 reviews

Instructor

Avatar

Laurence Moroney

AI Advocate
Google Brain

About deeplearning.ai

deeplearning.ai is Andrew Ng's new venture which amongst others, strives for providing comprehensive AI education beyond borders....

Frequently Asked Questions

  • Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.

  • This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.

  • This Specialization doesn't carry university credit, but some universities may choose to accept Specialization Certificates for credit. Check with your institution to learn more.

  • Yes, if you paid a one-time $49 payment for one or more of the courses, you can still subscribe to the Specialization for $49/month. If you pay for one course, you will have access to it for 180 days, or until you complete the course. If you subscribe to the Specialization, you will have access to all four courses until you end your subscription.

More questions? Visit the Learner Help Center.