Andrew Ng's five-course deep-learning programme, the standard path into neural networks. It builds from the basics up through convolutional and sequence models, with hands-on coding. It is more advanced than his Machine Learning Specialization, so most people take that one first.
Good for: Learners who know some Python and machine-learning basics and want to go deep on neural networks.
Less suitable if: You are new to machine learning, or you want a quick overview rather than five courses.
Skills you'll gain
Deep learningNeural networksConvolutional networksSequence modelsTensorFlowHyperparameter tuning
Is this course right for you?
A good fit if you…
You have machine-learning basics and some Python
You want a thorough grounding in neural networks
You can commit a few months
Consider something else if you…
You are new to machine learning
You want a short overview
You want the very latest research topics
Requirements: Basic Python and machine-learning fundamentals; intermediate level.
Realistic time: Around 120 hours across five courses; four to six months part-time.
About this course
The Deep Learning Specialization is the natural follow-on to Andrew Ng's Machine Learning Specialization and goes deep into neural network design and training: implementing networks from scratch in NumPy to understand the math, then applying them at scale with TensorFlow. Five courses cover neural network foundations, improving networks (hyperparameter tuning, regularization, optimization), structuring ML projects (the practical decision-making most courses skip), convolutional networks for vision, and sequence models for NLP and audio.
What you'll learn
Implement neural networks from scratch in NumPy to understand backpropagation
Apply regularization, optimization, and hyperparameter tuning effectively
Make systematic decisions about ML project strategy and error analysis
Build CNNs for object detection, segmentation, and face recognition
Build RNNs and attention models for NLP and sequence tasks
This course includes
130h
On-demand video
Yes
Certificate
Yes
Mobile access
English
Language
What it costs
On Coursera by subscription, about $49 a month. Most people finish the five courses in four to six months, so the total is often a few hundred dollars. A free audit of the videos is usually available.
Comparison · LBS
Compare alternatives for Deep Learning Specialization
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.
COCoursera4.8(147,000)
Deep Learning Specialization
Price
Paid
Free to audit, paid certificate
Duration
130 hrs
Level
Intermediate
Certificate
Specialization
DADataCamp4.6(5,000)
Machine Learning Scientist with Python Career Track
The specialisation certificate comes from Coursera with DeepLearning.AI. It is well regarded in the field, but employers still want to see projects — the coding practice you do here is the real asset.
Instructor
AN
Andrew Ng
Coursera instructor
1.3M+ learners12 courses4.9 instructor rating
Taught by Andrew Ng, Co-founder of Coursera and DeepLearning.AI, former Head of AI at Baidu and Google Brain, the most-trusted ML educator of the last decade.
Take the Machine Learning Specialization first if you are newer — it is the gentler introduction. This Deep Learning Specialization is the more advanced, neural-network-focused follow-on.
It runs on a Coursera subscription of about $49 a month; finishing in four to six months puts the total in the low hundreds. You can audit the videos free.
Yes for a solid grounding in deep learning, especially with the hands-on coding. Pair it with your own projects.
Around 120 hours across five courses — four to six months at a part-time pace.
Some. It keeps the maths manageable, but comfort with the basics and Python helps a lot.