Current
Intermediate
40% Off
Neural Networks & Deep Learning
Coursera · deeplearning.AI / Andrew Ng · Updated March 2026
Platform rating
4.5/5
AI Tutor Rating
8.3/10
Duration
4 weeks, 7 hours/week
Classes
50
Dive into the fundamentals of neural networks and deep learning with mathematical foundations and practical implementations. Learn about activation functions, backpropagation, and optimization techniques. First course in Andrew Ng's Deep Learning Specialization.
What you'll get
Understand neural network architecture and forward/backward propagation
Implement neural networks from scratch and with frameworks
Master activation functions, loss functions, and optimization
Apply deep learning to classification and regression problems
Build and train neural networks with TensorFlow
Fit
Best for
Leaders
Analysts
Researchers
Decision-makers
Not ideal for
Learners seeking only entry-level overviews
Prerequisites & pricing
Prerequisites
Linear algebra, calculus, and Python programming
Pricing
Free to audit, $49 for certificate
Certification
Certificate
Growth Leverage: Completing this course positions individuals for roles such as Machine Learning Engineer, Data Scientist, or AI Specialist, allowing them to pursue certifications like TensorFlow Developer. It opens doors to industries such as finance, healthcare, and tech, where deep learning expertise is increasingly essential.
Skills Value: The skills learned, particularly in TensorFlow, command high salaries, with AI/ML roles averaging $120,000 to $150,000 annually due to the demand for expertise in neural networks. Employers seek these skills to solve complex problems in image and speech recognition, predictive analytics, and automation.
deep-learning
neural-networks
tensorflow
backpropagation
optimization
artificial-intelligence