Intermediate Deep Learning Certification
Advanced neural networks, optimization techniques, and practical deep learning implementations
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Questions
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Pass Score
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Time Limit
You've earned this certification!
What You'll Demonstrate
- Build and train deep neural networks from scratch
- Implement optimization algorithms and regularization techniques
- Master convolutional neural networks for computer vision
- Apply best practices for deep learning model design
- Build production-ready deep learning models
Topics Covered by This Exam
Neural Network Fundamentals
90 minutes
Activation Functions Deep Dive
45 minutes
Loss Functions and Optimization
60 minutes
Stochastic Gradient Descent
75 minutes
Variance Reduction in SGD
60 minutes
Hyperparameters and Regularization
90 minutes
Training Deep Networks in PyTorch
120 minutes
Training Deep Networks in TensorFlow
120 minutes
Practical Guide to Deep Network Design
90 minutes
Vanishing and Exploding Gradients
75 minutes
Normalization Techniques
60 minutes
Residual Connections
60 minutes
Residuals and Normalizations Combined
75 minutes
Convolutional Neural Networks
150 minutes
Structure of Convolutions
90 minutes
Pooling Layers
60 minutes
Design Principles of CNNs
90 minutes
CNNs in PyTorch
120 minutes
Deep Representations
75 minutes
Dilation and Upconvolution
90 minutes
Dilation and Upconvolution in PyTorch
90 minutes
Advanced Deep Learning Training
120 minutes
Computer Vision Project
240 minutes
Adaptive Exam Format
Progressive Difficulty
Questions advance from Easy → Medium → Hard as you proceed through the exam
Single & Multi Select
Mix of single-answer and multi-answer questions to assess depth of knowledge
Randomised Bank
Questions are drawn randomly from a larger question bank — no two exams are the same
Badge & Certificate
Digital badge and printable certificate issued immediately upon passing
Schedule Your Exam
- Digital badge on your profile
- Printable certificate PDF
- Shareable credential link
- Unlimited retakes