CNN Study Guide 2026

Everything you need to pass the CNN exam in one place: the exam format, every topic to study, real practice questions with explanations, flashcards, and full-length practice tests. Free, no sign-up needed.

CNN exam key facts

The Certified Nephrology Nurse (CNN) exam consists of 150 questions. Source
The CNN exam must be completed in three hours. Source
Candidates must receive a standard score of 95 to pass the CNN examination. Source
The CNN exam application fee is $350 for non-members and $300 for ANNA, NOVA, ASN or NKF members. Source
A CNN candidate who does not pass has one opportunity within one year to retake the exam at a reduced rate. Source
The CNN credential is valid for three years from the last day of the month in which the certificant passed the exam. Source

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📋 CNN Exam Format at a Glance

150

Questions

180 min

Time Limit

70%

Passing Score

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📚 CNN Topics to Study (31)

Architecture Fundamentals · 7 cards Architecture Fundamentals · 7 cards Architecture Fundamentals · 7 cards Architecture Fundamentals · 7 cards Batch Normalization and Dropout · 7 cards Classic CNN Architectures · 7 cards Convolutional Layer Operations · 7 cards Object Detection Models · 7 cards Overfitting and Regularization · 7 cards Pooling and Activation Functions · 7 cards Training and Optimization · 7 cards Transfer Learning with CNNs · 7 cards Visualizing CNN Feature Maps · 7 cards Certified Nephrology Nurse · 7 cards Certified Nephrology Nurse · 7 cards Certified Nephrology Nurse · 7 cards CNN - Convolutional Neural Networks Data Augmentation Techniques Questions and Answers · 6 cards CNN - Convolutional Neural Networks Data Augmentation Techniques Questions and Answers · 6 cards CNN - Convolutional Neural Networks Data Augmentation Techniques Questions and Answers · 6 cards CNN - Convolutional Neural Networks Semantic Segmentation Questions and Answers · 6 cards CNN - Convolutional Neural Networks Semantic Segmentation Questions and Answers · 6 cards CNN - Convolutional Neural Networks Semantic Segmentation Questions and Answers · 6 cards Classic CNN Architectures · 6 cards Architecture Fundamentals · 6 cards Convolutional Layer Operations · 6 cards Object Detection Models · 6 cards Overfitting and Regularization · 6 cards Pooling and Activation Functions · 6 cards Training and Optimization · 6 cards Transfer Learning with CNNs · 6 cards

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✍️ Sample CNN Questions & Answers

1. What filter size does VGGNet use exclusively in its convolutional layers?

✓ 3x3

VGGNet uses only 3x3 convolutional filters, showing that stacking small filters achieves the same receptive field as larger filters with fewer parameters.

2. How does a transposed convolution (sometimes called deconvolution) differ from a standard convolution in terms of spatial output?

✓ It increases spatial dimensions, making it useful for upsampling

Transposed convolution is the gradient operation of a forward convolution; it increases spatial size and is used in decoders, GANs, and segmentation networks.

3. The gradient of a substance's concentration, such as urea, during peritoneal dialysis

✓ Decreases

During peritoneal dialysis, the dialysate solution is introduced into the peritoneal cavity, creating a concentration gradient for waste products like urea. Initially, urea concentration is high in the blood and low in the dialysate. As dialysis progresses, urea moves from the blood into the dialysate, causing its concentration in the blood to decrease and its concentration in the dialysate to increase, thus reducing the overall concentration gradient over time until equilibrium is approached.

4. The VGGNet architecture is renowned for its simplicity and depth. What is the defining characteristic of its convolutional layers?

✓ It exclusively uses very small 3x3 filters stacked on top of each other.

The key innovation and defining feature of the VGG architecture is its uniformity and simplicity, achieved by exclusively using small 3x3 convolutional filters stacked to increase the network's depth. This approach increases the effective receptive field and allows for learning more complex features with more non-linearities, while keeping the number of parameters manageable.

5. What are dilated (atrous) convolutions and why are they used in semantic segmentation?

✓ Convolutions with gaps between kernel elements that expand the receptive field without increasing parameters or losing resolution

Dilated convolutions insert zeros between kernel weights (dilation rate > 1), allowing the filter to cover a larger area of the input without downsampling, which is critical for maintaining spatial resolution in segmentation.

6. Which layer type in a CNN is responsible for introducing non-linearity?

✓ Activation layer

Activation layers (e.g., applying ReLU) introduce non-linearity after convolution, enabling the network to learn complex patterns.

🎯 Free CNN Practice Tests

Architecture Fundamentals · 7 questions Object Detection Models · 7 questions Certified Nephrology Nurse · 7 questions Certified Nephrology Nurse · 7 questions Certified Nephrology Nurse · 7 questions Transfer Learning with CNNs · 7 questions Architecture Fundamentals · 7 questions Architecture Fundamentals · 7 questions Architecture Fundamentals · 7 questions Overfitting and Regularization · 7 questions

📖 CNN Guides & Articles

Your CNN Study Path

1. Learn with Flashcards → 2. Drill Practice Tests → 3. Take the Full Exam Simulation

🃏 CNN Flashcards (202)🏆 CNN Exam Simulation

What Practice Test Geeks adds beyond an AI chat for CNN

An AI chatbot can quiz you, but it can't reproduce the exam conditions or keep your record. Here you get:

A timed, full-length CNN mock exam — 150 questions in 180 minutes with a 70% pass mark, modeled on the official exam's question count and time limit, followed by a score report broken down by exam domain.
A fixed CNN question bank: the same test every attempt, so your score is comparable from one try to the next instead of changing with every regenerated quiz.
Progress saved on your device: completed tests, scores and missed questions stay in My Progress, so you can retake only what you got wrong.
A printable CNN cheat sheet you can print or save as a PDF.
CNN flashcards built from the same question bank.
Free CNN practice tests with the correct answer shown after each question.

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How this page was made: written with AI tools and published by Nathan Beja, founder of Practice Test Geeks, who is responsible for its content. Exam facts are checked against the official sources listed below. Not reviewed by a subject-matter expert. Editorial policy

Sources & references

Exam facts on this page (fees, format, dates, passing scores) are checked against these official sources; the date is our last check. Editorial policy

nncc-exam.org — Fees, retake policy, score release, test dates, score validity, exam format, passing score, time limit · verified Oct 2026