TensorFlow: Advanced Techniques Specialization

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  If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

• Can I just enroll in a single course?

  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.

• Is financial aid available?

  Yes, 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. Learn more.

• Can I take the course for free?

  When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.

• Is this course really 100% online? Do I need to attend any classes in person?

  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.

• What is TensorFlow?

  TensorFlow is an end-to-end opensource platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML, and developers easily build and deploy ML-powered applications.

• What are the applications of TensorFlow?

  TensorFlow is commonly used for machine learning applications such as voice recognition and detection, Google Translate, image recognition, and natural language processing.

• Why is TensorFlow important?

  TensorFlow is one of the most commonly used open-source libraries used for building and deploying ML models.

• What is the TensorFlow specialization about?

  The DeepLearning.AI TensorFlow: Advanced Techniques Specialization introduces the features of TensorFlow that provide learners with more control over their model architecture and tools that help them create and train advanced ML models.  

  In this Specialization, you will expand your knowledge of the Functional API and build exotic non-sequential model types. You will learn how to optimize training in different environments with multiple processors and chip types and get introduced to advanced computer vision scenarios such as object detection, image segmentation, and interpreting convolutions. You will also explore generative deep learning including the ways AIs can create new content from Style Transfer to Auto Encoding, VAEs, and GANs.

• I’ve already completed the DeepLearning.AI TensorFlow Developer Professional Certificate. What else will I learn in this Specialization?

  The DeepLearning.AI TensorFlow Developer Professional Certificate equips you with the foundational knowledge to create entry-level TensorFlow models using the Sequential API and prepares you for the Google TensorFlow Developer Certificate exam. 

  In this new TensorFlow Specialization, you will expand your skill set and take your understanding of TensorFlow techniques to the next level. You will learn how to use the Functional API for custom training, custom layers, and custom models. You will be equipped to master TensorFlow in order to build powerful applications for complex scenarios.

• What will I learn in this Specialization?

  Specialization: Gain practical knowledge of and hands-on training in advanced TensorFlow techniques such as style transfer (paint one picture in the style of another), object detection (detect where an object is in a picture), and generative machine learning (generating new images from scratch).

  Course 1: Understand the underlying basis of the Functional API and build exotic non-sequential model types, custom loss functions, and layers. 

  Course 2: Learn how optimization works and how to use GradientTape and Autograph. Optimize training in different environments with multiple processors and chip types.

  Course 3: Practice object detection, image segmentation, and visual interpretation of convolutions.

  Course 4: Explore generative deep learning and how AIs can create new content, from Style Transfer through Auto Encoding and VAEs to Generative Adversarial Networks.

• Who is the TensorFlow Specialization for?

  The TensorFlow: Advanced Techniques Specialization provides an accessible pathway for early and mid-career software and machine learning engineers with a foundational knowledge of TensorFlow looking to master TensorFlow by teaching them how to use advanced features in order to expand their skill set and build powerful models.

• What background knowledge is necessary?

  Learners should have a working knowledge of AI and deep learning. They should have intermediate Python skills (understanding of decorators and context managers is preferred) as well as some experience with any deep learning framework (TensorFlow, Keras, or PyTorch). Learners should be proficient in basic calculus, linear algebra, and statistics.

  We highly recommend that you complete the Deep Learning Specialization prior to starting this Specialization.

• What will I be able to do upon completing the Specialization?

  After completing this Specialization, you will gain practical knowledge and hands-on training in advanced TensorFlow techniques such as style transfer, object detection, and generative machine learning.

• Who created the TensorFlow Specialization?

  This Specialization was created by Laurence Moroney. 

  Laurence leads AI Advocacy at Google, with a vision to make AI easy for developers and to widen access to ML careers for everyone. He’s written dozens of programming books, the most recent being ‘AI and ML for Coders’ at O’Reilly. Laurence believes that MOOCs are one of the greatest ways to learn, and is excited to create TensorFlow Specializations with DeepLearning.AI on Coursera. 

  When not working with technology, he’s an active member of the Science Fiction Writers of America and has authored several sci-fi novels and comics books and a produced screenplay. Laurence is based in Washington state, where he drinks way too much coffee.

• Is this a standalone course or a Specialization?

  This is a Specialization made up of 4 courses.

• Do I need to take the courses in a specific order?

  We recommend taking the courses in the prescribed order for a logical and thorough learning experience.

• Can I audit this Specialization?

  You can audit the courses in the Specialization for free. You will not receive a certificate at the end if you choose to audit it for free instead of purchasing it.

• How long does it take to complete the Specialization?

  This Specialization consists of four courses. At the rate of 5 hours a week, it typically takes 3-4  weeks to complete each course.

• Will I earn university credit for completing the Specialization?

  No

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