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Introduction to TensorFlow for AI, ML and Deep Learning

Master TensorFlow fundamentals for building neural networks and computer vision applications.Introduction to TensorFlow for Artificial Intelligence.

Master TensorFlow fundamentals for building neural networks and computer vision applications.Introduction to TensorFlow for Artificial Intelligence.

This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full DeepLearning.AI TensorFlow Developer Professional Certificate program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.

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Instructors:

English

پښتو, বাংলা, اردو, 2 more

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Introduction to TensorFlow for AI, ML and Deep Learning

This course includes

22 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free

What you'll learn

  • Build and train basic neural networks using TensorFlow

  • Implement computer vision applications with deep learning

  • Master convolutional neural networks for image processing

  • Develop practical skills in handling real-world image data

Skills you'll gain

TensorFlow
Neural Networks
Computer Vision
Machine Learning
Deep Learning
Convolutional Networks
Image Processing
Python Programming
Data Science
AI

This course includes:

1.3 Hours PreRecorded video

4 assignments

Access on Mobile, Tablet, Desktop

FullTime access

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There are 4 modules in this course

This comprehensive course introduces TensorFlow, Google's popular open-source framework for machine learning and deep learning. Students learn to build and train neural networks, starting with basic concepts and progressing to computer vision applications with convolutional neural networks. The curriculum includes hands-on programming exercises using real-world datasets, covering essential topics like callbacks, data handling, and image processing. Through practical labs and guided projects, participants gain experience implementing computer vision solutions and working with complex image data.

A New Programming Paradigm

Module 1 · 5 Hours to complete

Introduction to Computer Vision

Module 2 · 5 Hours to complete

Enhancing Vision with Convolutional Neural Networks

Module 3 · 5 Hours to complete

Using Real-world Images

Module 4 · 6 Hours to complete

Fee Structure

Instructor

Laurence Moroney
Laurence Moroney

5 rating

9 Reviews

5,22,923 Students

19 Courses

Pioneering AI Educator and Best-Selling Author

Laurence Moroney is an award-winning artificial intelligence researcher and best-selling author dedicated to making AI and machine learning accessible to everyone. As an instructor at DeepLearning.AI, he has taught millions through MOOCs and YouTube, while also serving as a keynote speaker at various events. Moroney is a fellow of the AI Fund and advises several AI startups, leveraging his expertise to foster innovation in the field. Based in Seattle, Washington, he is also an active member of the Science Fiction Writers of America, having authored multiple sci-fi novels and comic books. When not immersed in technology, he enjoys indulging in coffee and exploring creative writing.

Introduction to TensorFlow for AI, ML and Deep Learning

This course includes

22 Hours

Of Self-paced video lessons

Intermediate Level

Completion Certificate

awarded on course completion

Free

Testimonials

Testimonials and success stories are a testament to the quality of this program and its impact on your career and learning journey. Be the first to help others make an informed decision by sharing your review of the course.

4.8 course rating

19,440 ratings

Frequently asked questions

Below are some of the most commonly asked questions about this course. We aim to provide clear and concise answers to help you better understand the course content, structure, and any other relevant information. If you have any additional questions or if your question is not listed here, please don't hesitate to reach out to our support team for further assistance.