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Introduction to TensorFlow for AI, ML and Deep Learning
Intermediate English Professional CertificateFREE
Our recommendation
The practical counterpart to theory-first courses: instead of deriving the maths, you start building working models in TensorFlow almost immediately, guided by Laurence Moroney. It is the first course in DeepLearning.AI's TensorFlow Developer Professional Certificate on Coursera. Hands-on and approachable, though it assumes you already grasp the basics of neural networks.
Good for: Getting hands-on with TensorFlow quickly, after some ML grounding.
Less suitable if: You have never met neural networks, or you want the underlying theory.
Requirements: Basic Python and a grasp of what neural networks are (Andrew Ng's course pairs well as a precursor).
Realistic time: Around 18–20 hours over a few weeks.
About this course
Introduction to TensorFlow for AI, ML and Deep Learning is the practical counterpart to theory-first courses: instead of deriving the maths, you start building working models in TensorFlow almost immediately. Laurence Moroney walks through writing your first neural networks, training an image classifier, and using convolutions to improve computer-vision results.
What you'll learn
Write and train your first neural network in TensorFlow
Build an image classifier end to end
Use convolutions and pooling to improve vision models
Prevent overfitting with practical techniques
Work with real image datasets in code
Read and adapt TensorFlow training code with confidence
This course includes
Yes
Certificate
Yes
Mobile access
English
Language
What it costs
Free to audit on Coursera. A certificate needs a Coursera subscription (about $49/month) or Coursera Plus, with financial aid available. It is the first of four courses in the DeepLearning.AI TensorFlow Developer Professional Certificate.
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COCoursera
Introduction to TensorFlow for AI, ML and Deep Learning
The DeepLearning.AI TensorFlow Developer Professional Certificate on Coursera is well regarded. Note it is separate from Google's official TensorFlow Developer Certificate exam, which Google retired in 2024.
Last updated
Google retired its standalone TensorFlow Developer Certificate exam in 2024; this Coursera professional certificate is a separate, still-active programme.
Instructor
LM
Laurence Moroney
Coursera instructor
Laurence Moroney leads AI Advocacy at Google and is the author of several TensorFlow books. He's known for a code-first, plain-spoken teaching style that gets beginners building real models quickly rather than getting stuck in theory.
No. Google retired its standalone TensorFlow Developer Certificate exam in 2024. This is DeepLearning.AI's Coursera professional certificate, which is separate and still active.
Yes, some grounding helps — it is practical rather than theory-first. Andrew Ng's Deep Learning course is a good precursor.
You can audit it free; the certificate requires a Coursera subscription or Coursera Plus.
Yes, basic Python is expected since you build models in code.
Yes — it is the first of four courses in the DeepLearning.AI TensorFlow Developer Professional Certificate.