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Deep Learning Specialization (Andrew Ng)

120 hours
4.9(112,000 reviews)
Free

Andrew Ng's Deep Learning Specialization is a Coursera program you take at coursera.org. You can audit all five courses for free, which gives you the video lectures and readings. The programming assignments, quizzes, and the certificate need a Coursera subscription or per-course payment, and financial aid is available. DeepLearning.AI builds and hosts it on Coursera, so there is no separate free version elsewhere. We are not in Coursera's affiliate program, so we earn nothing whether you audit or pay. Audit it if you want the lectures for free, or pay for the full track if you want the graded coding assignments, which are where most of the learning happens.

Over 1 million learners have enrolled, and the specialization is rated 4.9 out of 5 from more than 120,000 reviews (source: coursera.org/specializations/deep-learning).

About This Course

Andrew Ng's landmark Deep Learning Specialization on Coursera. Five courses covering neural networks, CNNs, RNNs, optimisation, and ML strategy. Free to audit; certificate costs money.

Course Details

Platform

Coursera

Level

advanced

Duration

120h

Certificate

Yes, included

Cost

Free

Frequently Asked Questions

Can I take the Deep Learning Specialization free?

You can audit the lectures free. The graded coding assignments and the certificate require payment or Coursera financial aid.

What are the prerequisites?

Comfortable Python and basic math (linear algebra and some calculus). It's an advanced series, not a first machine learning course.

What does it cover?

Neural networks, deep networks, hyperparameter tuning, CNNs for computer vision, and RNNs for sequences, plus practical machine learning project strategy.

Is auditing enough, or do I need to pay?

The lectures teach the theory, but the graded assignments are where you build the models. Pay for the full track if you want that practice and the certificate.

Do you get paid if I enroll?

No. We are not in Coursera's affiliate program, so we earn nothing either way. This one is on the list because it holds up, not because it pays.

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