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Deep Learning Specialization
Master neural networks from scratch
An intensive engineering track designed for those who want to build the future. We go beyond the APIs and frameworks to understand the calculus and linear algebra that powers modern AI. You will build neural networks from scratch before moving to PyTorch and TensorFlow.
4.9rating
1,200+students
12 Weeks
72lessons
Learning Outcomes
What You'll Learn
Master the math behind Neural Networks
Build and deploy models using PyTorch
Understand state-of-the-art architectures
Complete a production-level Portfolio Project
Contribute to open-source ML projects
Interview confidently for ML engineering roles
Curriculum
Course Content
Build neural networks from first principles
Logistic RegressionBackpropagationGradient Descent
Target Audience
Who Is This Course For?
Software Engineers
Developers wanting to transition to ML
Data Scientists
Analysts seeking deeper technical skills
Researchers
Academics exploring practical ML
AI Enthusiasts
Self-learners with strong math background