Neural Networks and Deep Learning
Neural Networks and Deep Learning is an intermediate-level online course from Coursera in Deep Learning. It is structured in 4 modules, over 24h 35m. Learners rate it 4.9/5 from 123.8K ratings on Coursera.
Part of our Deep Learning courses collection, where we compare it against 2 other courses.
Course highlights
| Provider | Coursera |
| Duration | 24h 35m |
| Level | Intermediate |
| Mode | Self-paced |
| Language | English |
| Certificate | Yes — shareable certificate |
| Rating | 4.9★ (123.8K reviews) |
| Price | Check price |
About this course
The Neural Networks and Deep Learning course from Coursera teaches the foundational concepts of building neural networks. This course is the first in the Deep Learning Specialization offered by DeepLearning.AI. It begins with an introduction to Deep Learning, then moves into the basics of neural networks. You will explore both shallow neural networks and deep neural networks, understanding their structure and how they learn.
This self-paced course helps you develop skills in Artificial Neural Networks, Deep Learning, and Supervised Learning. You will learn about Model Training and Model Optimization, which are key steps in developing effective AI models. The curriculum also introduces Python Programming in the context of deep learning, along with concepts like Artificial Intelligence and Machine Learning (AI/ML) methods. By the end, you will have a solid grasp of how these complex systems function.
Upon completing this course, you will be able to explain the core principles behind neural networks and deep learning. You can apply basic Python programming to implement simple neural network models. You will also understand the differences between shallow and deep architectures. This foundation prepares you for more advanced topics in applied machine learning and specific neural network types like Convolutional Neural Networks.
This is a Beginner-level course, designed for learners who have intermediate Python skills, including familiarity with basic programming, loops, if/else statements, and data structures. A basic grasp of linear algebra and machine learning concepts is also helpful. If you are new to programming or foundational mathematics, you may need to cover those areas first. For those looking to dive deeper into specific frameworks, the Deep Learning with Keras and Tensorflow course on Coursera offers practical implementation using popular libraries. To explore other areas of study, you can visit our main Deep Learning courses hub. Alternatively, if you are interested in specialized applications, consider the Brain-Computer Interface (BCI) Masterclass on Udemy.
Level and time commitment
- Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
- A basic grasp of linear algebra & ML
Skills you’ll gain
What this course covers
4 modulesThe 4-part outline Coursera publishes for this course, across 24h 35m.
Module 1 · Introduction to Deep Learning
Module 2 · Neural Networks Basics
Module 3 · Shallow Neural Networks
Module 4 · Deep Neural Networks
What learners rate it
Rated 4.9/5 by 123.8K learners on Coursera (checked 6 Nov 2026).
This rating is collected by Coursera from its own enrolled learners. We reproduce it as reported and do not accept paid or incentivised reviews. See it on Coursera →
Compiled by the CoursesGlobal editorial desk. Fees, ratings, duration and certificate details for the 1 course shown are read directly from Coursera course pages — we never estimate a price or a rating. Last verified 6 November 2026.
How we compare and rank courses · Our review policy · Affiliate disclosure
Compare with alternatives
Same topic, different trade-offs — here's who runs each one and what it's best at.
| Course | Provider | Rating | Price | Duration | Why pick this one | |
|---|---|---|---|---|---|---|
| Neural Networks and Deep Learning This |
 Coursera
|
4.9★ | Check price | 24h 35m | Highest rated (4.9★ from 123.8K reviews) | |
| Deep Learning with Keras and Tensorflow |
Coursera
|
4.4★ | Check price | 23h 21m | For learners past the basics · 23h 21m | View ↗ |
| Brain-Computer Interface (BCI) Masterclass |
 Udemy
|
4★ | ₹459 | 4.5 hours | Most popular — 18.2K learners | View ↗ |
Where Deep Learning leads
Roles we map to Deep Learning on CoursesGlobal. This is our own mapping of subject to job, not a placement claim by Coursera.
Browse every course we track for one of these — courses for data scientists.
Common questions
How much does Neural Networks and Deep Learning cost?
Coursera does not publish a price we can read on the course page, so we do not show one. Check the fee on the provider site — we would rather say nothing than quote a number we did not collect.
Does Neural Networks and Deep Learning come with a certificate?
Yes — Coursera lists a certificate on completion. It is a course certificate, not a formal qualification or university credit.
How long does Neural Networks and Deep Learning take?
Coursera lists it at 24h 35m. It is self-paced, so that is the volume of material rather than a deadline — how long it actually takes depends on the hours you put in each week.
Is Neural Networks and Deep Learning suitable for beginners?
Coursera lists it at Intermediate level, so it assumes some grounding in the subject already. If you are starting from zero, a beginner-level course in the same topic is the better entry point.
What does Neural Networks and Deep Learning cover?
It is organised into 4 modules, starting with Introduction to Deep Learning and going on to Neural Networks Basics, Shallow Neural Networks, Deep Neural Networks. The full outline is on this page.