CODeepLearning.AI · on Coursera
Introduction to TensorFlow for AI, ML and Deep Learning
Intermediate English Professional CertificateFREE
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
Comparison · LBS
Compare alternatives for Introduction to TensorFlow for AI, ML and Deep Learning
Same topic, different options. We surface the trade-offs others hide so you can pick the course that actually fits your time, budget, and goals.
COCoursera—(0)
Introduction to TensorFlow for AI, ML and Deep Learning
- Price
- FreeAudit free · Certificate available
- Duration
- —
- Level
- Intermediate
- Certificate
- Professional
COCoursera4.9(78,000)
Machine Learning Specialization
- Price
- FreeAudit free · Cert $49/mo
- Duration
- 94 hrs
- Level
- Intermediate
- Certificate
- Professional
COCoursera4.8(12,400)
AWS Certified AI Practitioner
- Price
- FreeAudit free · Cert $49/mo
- Duration
- 14 hrs
- Level
- Beginner
- Certificate
- Professional
COCoursera4.8(24,100)
Generative AI for Everyone
- Price
- FreeAudit free · Cert $49
- Duration
- 6 hrs
- Level
- Beginner
- Certificate
- Professional
Prices and ratings refreshed daily. We're not affiliated with any single provider.
Instructor
LM
Laurence Moroney
Coursera instructor
— learners— courses — instructor rating
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.
Requirements
- Comfortable with Python
- Some ML/deep-learning concepts help (e.g. from Andrew Ng's courses)
Who this course is for
- Developers ready to build models, not just study them
- Learners who finished a concepts course and want hands-on practice
- Engineers adding deep learning to their toolkit
About this provider
CO
Coursera
University-backed online learning platform. 142M learners, 7,000+ courses from 325+ institutions.
4.6 trust score
Frequently asked questions
It helps. The course is hands-on and assumes you grasp the basic idea of a neural network — many learners take a concepts course (like Andrew Ng's) first, then this to learn the tooling.
Comfort with Python is the main requirement. A little machine-learning background makes the pace easier but isn't strictly necessary.
You can audit it free on Coursera. The certificate and graded coding assignments require a subscription.
Both — you learn TensorFlow by building real models (image classifiers, CNNs), so you come away with practical skills, not just API memorisation.
The concepts transfer either way. TensorFlow remains widely used in industry, and once you understand the workflow here, picking up PyTorch later is straightforward.