CNN Practice Test
Updated October 2026Facts verified Oct 25, 2026 against Nephrology Nursing Certification Commission (NNCC), with C-NET (Center for Nursing Education and Testing) as test admini
The CNN has 150 questions, takes about 3 hours and costs $350[1][2] (Nephrology Nursing Certification Commission (NNCC), with C-NET (Center for Nursing Education and Testing) as test admini, verified Oct 25, 2026).
- The Certified Nephrology Nurse (CNN) exam consists of 150 questions.[1]
- The CNN exam must be completed in three hours.[1]
- Candidates must receive a standard score of 95 to pass the CNN examination.[1]
- The CNN exam application fee is $350 for non-members and $300 for ANNA, NOVA, ASN or NKF members.[2]
- A CNN candidate who does not pass has one opportunity within one year to retake the exam at a reduced rate.[2]
- The CNN credential is valid for three years from the last day of the month in which the certificant passed the exam.[2]
- CNN candidates taking the computer-based test receive their score immediately upon completion.[2]
Numbers in brackets link to the official sources listed under Sources & last verified. Dates that have passed are removed automatically.
CNN Exam at a Glance
What changed for CNN in 2026
- Oct 25, 2026: Passing score changed to Standard score of 95 (previously Standard score of 95 (about 70% correct)).[1]
- Oct 25, 2026: Exam fee changed to $350 ($300 for ANNA/NOVA/ASN/NKF members) (previously $350 ($300 for partner-organization members)).[2]
- Oct 25, 2026: Testing window changed to 90-day window from permit issue (previously Year-round computer-based testing; test within a 90-day window after approval).[2]
Note: To sit for the CNN exam, you must have at least 3,000 hours of experience in nephrology nursing within the last three years and hold a current, unrestricted RN license.
CNN Exam Study Guide
Use this interactive guide to understand the key components of the Certified Nephrology Nurse exam, from registration to scoring.
Many dialysis organizations (like DaVita or Fresenius) and hospitals offer reimbursement for certification exams. Check with your HR department before paying out of pocket. Practice with the free CNN - Convolutional Neural Networks practice test on PracticeTestGeeks (7 questions with answer explanations).
Free CNN - Convolutional Neural Networks Study Tools
Interactive CNN - Convolutional Neural Networks resources on PracticeTestGeeks, free to start:
- CNN - Convolutional Neural Networks flashcards — review key terms and concepts card by card
- CNN - Convolutional Neural Networks study guide — topic-by-topic overview of what the exam covers
- CNN - Convolutional Neural Networks cheat sheet — one-page printable summary for last-minute review
According to Nephrology Nursing Certification Commission (NNCC), with C-NET (Center for Nursing Education and Testing) as test admini, “The CNN exam consists of 150 questions and must be completed in three (3) hours.”[1]
CNN Practice Test Questions
Prepare for the CNN - Convolutional Neural Networks exam with our free practice test modules. Each quiz covers key topics to help you pass on your first try.
CNN Batch Normalization and Dropout
Free CNN Practice Test featuring Batch Normalization and Dropout. Improve your CNN Exam score with mock test prep.
CNN - Convolutional Neural Networks Data A...
CNN Test Prep for CNN - Convolutional Neural Networks Data Augmentation Techniques Questions and Answers. Practice CNN Quiz questions and boost your score.
CNN - Convolutional Neural Networks Semant...
CNN Questions and Answers on CNN - Convolutional Neural Networks Semantic Segmentation Questions and Answers. Free CNN practice for exam readiness.
CNN - Convolutional Neural Networks Classi...
Free CNN Quiz on - Convolutional Neural Networks Classic CNN Architectures. CNN Exam prep questions with detailed explanations.
CNN - Convolutional Neural Networks CNN Ar...
CNN Practice Questions for - Convolutional Neural Networks CNN Architecture Fundamentals. Build confidence for your CNN certification exam.
CNN - Convolutional Neural Networks Convol...
CNN Test Online for - Convolutional Neural Networks Convolutional Layer Operations. Free practice with instant results and feedback.
CNN - Convolutional Neural Networks Object...
CNN Study Material on - Convolutional Neural Networks Object Detection Models. Prepare effectively with real exam-style questions.
CNN - Convolutional Neural Networks Overfi...
Free CNN Test covering - Convolutional Neural Networks Overfitting and Regularization. Practice and track your CNN exam readiness.
CNN - Convolutional Neural Networks Poolin...
CNN Exam Questions covering - Convolutional Neural Networks Pooling and Activation Functions. Master CNN Test concepts for certification prep.
CNN - Convolutional Neural Networks Traini...
Free CNN Practice Test featuring - Convolutional Neural Networks Training and Optimization. Improve your CNN Exam score with mock test prep.
CNN - Convolutional Neural Networks Transf...
CNN Mock Exam on - Convolutional Neural Networks Transfer Learning with CNNs. CNN Study Guide questions to pass on your first try.
CNN - Convolutional Neural Networks Visual...
CNN Test Prep for - Convolutional Neural Networks Visualizing CNN Feature Maps. Practice CNN Quiz questions and boost your score.
CNN Certified Nephrology Nurse MCQ
Free CNN Test covering Certified Nephrology Nurse MCQ. Practice and track your CNN exam readiness.
Worked examples: how to reason through CNN questions
These are practice questions written for this site, not questions from the real exam. Each explanation shows why the right answer is right and why the others are wrong.
Example 1
Question: What is the primary motivation for 'freezing' the early convolutional layers of a pre-trained CNN when applying transfer learning to a new task?
- To significantly increase the training speed by reducing the number of backpropagation calculations.
- To preserve the generic, low-level feature detectors (e.g., edges, colors, textures) that the model learned from the original large-scale dataset.
- To force the model to learn new low-level features that are highly specific to the new, smaller dataset.
- To ensure that the optimizer can apply a uniform learning rate across all layers of the network.
Answer: B. To preserve the generic, low-level feature detectors (e.g., edges, colors, textures) that the model learned from the original large-scale dataset.
Explanation:
The correct answer is the option about preserving generic, low-level feature detectors. Early layers learn edges, colors and textures that are useful for almost any image task, so keeping their weights fixed protects that knowledge when the new dataset is small.
The speed option is wrong as a primary motivation: skipping some weight updates saves a little work, but that is a side effect, not the reason. The option about forcing new low-level features is backwards, because freezing prevents those layers from changing. The uniform learning rate option is wrong because freezing does not exist to simplify the optimizer; layers can be given different rates whether or not they are frozen.
Rule to remember: freeze the general, early layers and retrain the later, task-specific ones.
Example 2
Question: In VGGNet, what architectural choice was a key design principle?
- Using a single large 11×11 kernel in the first layer
- Stacking many small 3×3 convolutional filters instead of large kernels
- Applying global average pooling before the classifier
- Introducing residual skip connections between layers
Answer: B. Stacking many small 3×3 convolutional filters instead of large kernels
Explanation:
The correct answer is stacking many small 3×3 convolutional filters instead of large kernels. VGGNet showed that depth built from small filters works well. Stacked small filters cover the same receptive field as one larger filter while using fewer parameters and adding more non-linearity.
The single large 11×11 kernel option describes an older style of first layer, which VGGNet moved away from. Global average pooling before the classifier is a later design choice found in other networks, not the defining idea of VGGNet. Residual skip connections belong to ResNet, a different architecture.
Rule to remember: match each architecture to its signature idea. VGG is small filters stacked deep, and ResNet is skip connections.
Example 3
Question: Which operation sums element-wise products between a filter and a receptive field in a CNN?
- Cross-correlation
- Matrix multiplication
- Dot product of flattened tensors
- Convolution without flipping
Answer: A. Cross-correlation
Explanation:
The correct answer is cross-correlation. In a CNN layer, the filter slides over the input, and at each position the element-wise products with the receptive field are summed. The filter is not flipped, which is what separates this operation from true mathematical convolution. Deep learning libraries still call it convolution.
Matrix multiplication is wrong because it combines rows and columns of whole matrices, not a sliding local window. Dot product of flattened tensors describes the arithmetic at one position but not the sliding operation the question asks about. Convolution without flipping is a loose way of describing the same thing, but the precise name for it is cross-correlation, so it is not the best answer.
Rule to remember: sum of products with no flip is cross-correlation.
How to use these practice tests
Start with the official NNCC exam page and application, and read what the credential covers and how testing works. Our sets are written by us with AI tools and are not real exam questions, so use them to find weak spots, not to predict the test.
If you are preparing for the nursing credential, work through the Certified Nephrology Nurse sets first: the standard set, the MCQ set and the trivia set. Take one in a single sitting under the 3 hour limit that applies to the real exam, so you get used to the pace of 150 questions. Afterwards, read the explanation for every miss and for every guess you got right.
Keep a short list of the topics you missed and go back to the official material to study them, then retest on a different set. Do not simply repeat a set until you recognise the answers.
If you came here for convolutional neural networks, the sets on architectures, layers, pooling, training, regularization, transfer learning and object detection are separate from the nursing exam. Work through them by topic and check each missed idea against a textbook or course notes.
In the last days before your sitting, check that your permit is still active and that you know your testing arrangements.
CNN Career Opportunities
Explore the diverse roles available to Certified Nephrology Nurses.
Acute Care Nurse
Provide bedside dialysis (HD, CRRT, SLED) to critically ill patients in ICU and hospital settings. High acuity environment.
Outpatient Clinic Nurse
Manage chronic hemodialysis patients in community clinics. Build long-term relationships and manage regular treatments.
Home Therapy Nurse
Train and support patients performing Peritoneal Dialysis (PD) or Home Hemodialysis. Focus on patient education and independence.
Transplant Coordinator
Manage the complex process of kidney transplantation, from pre-transplant evaluation to post-operative follow-up and education.
Nurse Manager
Oversee operations, staffing, and regulatory compliance of a dialysis unit or nephrology department. Leadership role.
CNN Test Day Checklist
- ✓Valid Government ID
- ✓Exam Permit/Confirmation
- ✓RN License Number
- ✓Arrive 30 Mins Early
- ✓Leave Electronics in Car
- ✓Light Jacket (Testing centers get cold)
- ✓Water/Snack (for locker)
- ✓Positive Mindset!
Ready to Become a CNN?
Join thousands of successful nephrology nurses who advanced their careers with our free practice resources.
Keep track of your CE certificates as you earn them. The NNCC audits a percentage of renewals, so having your documentation ready prevents stress later.
CNN: Pros and Cons
- +CNN exam preparation strengthens your knowledge across all domains
- +Passing the exam proves competency to employers and clients
- +Study materials and practice tests are widely available
- +Exam-based credentials are portable across states and employers
- +Clear exam objectives help focus your study plan effectively
- −Exam anxiety can affect performance — practice tests help reduce it
- −Registration fees are non-refundable if you miss your test date
- −Limited retake opportunities may apply with waiting periods
- −Exam content updates periodically — use current study materials
- −Testing center availability may require advance scheduling
Pros and Cons at a Glance
| Pros | Cons |
|---|---|
| CNN exam preparation strengthens your knowledge across all domains | Exam anxiety can affect performance — practice tests help reduce it |
| Passing the exam proves competency to employers and clients | Registration fees are non-refundable if you miss your test date |
| Study materials and practice tests are widely available | Limited retake opportunities may apply with waiting periods |
| Exam-based credentials are portable across states and employers | Exam content updates periodically — use current study materials |
| Clear exam objectives help focus your study plan effectively | Testing center availability may require advance scheduling |
Sample CNN - Convolutional Neural Networks Practice Questions
Try these questions from our free CNN - Convolutional Neural Networks practice tests. The correct answer and an explanation follow each question.
A team is adapting a powerful ImageNet pre-trained model for a new task of classifying industrial machine parts from a large, proprietary dataset of over 200,000 images. The visual characteristics of the machine parts are significantly different from the natural images in ImageNet. What is the most effective transfer learning approach?
- A. Freeze the entire pre-trained model and only train a new classifier head.
- B. Discard the pre-trained weights and train the entire model from scratch on the new dataset.
- C. Unfreeze most or all of the layers and fine-tune the entire network using the pre-trained weights as a starting point.
- D. Use only the final fully connected layers from the pre-trained model and build a new convolutional base.
Answer: C. Unfreeze most or all of the layers and fine-tune the entire network using the pre-trained weights as a starting point.
Because the new dataset is large, there is less risk of overfitting. Since the data domain is different, the model needs to learn more specialized features. The optimal approach is to use the pre-trained weights as a superior alternative to random initialization and fine-tune the entire network, allowing it to adapt its learned features to the new domain of machine parts.
What does a feature map (activation map) represent in a CNN layer?
- A. The raw pixel values of the input image
- B. The output of applying a learned filter across the input
- C. The gradient of the loss with respect to weights
- D. The pooled output after max pooling only
Answer: B. The output of applying a learned filter across the input
A feature map is produced by convolving a learned filter over the input, showing where and how strongly that filter's pattern is detected.
What problem does data augmentation specifically help address during transfer learning fine-tuning?
- A. Catastrophic forgetting of source task
- B. Overfitting when the target dataset is small
- C. Slow convergence due to frozen layers
- D. Gradient explosion in deep layers
Answer: B. Overfitting when the target dataset is small
Data augmentation artificially expands the small target dataset, reducing overfitting during fine-tuning.
Which of the following is a key advantage of DETR over traditional CNN-based detectors?
- A. It uses more anchor boxes for better coverage
- B. It eliminates the need for NMS by using a transformer with set prediction
- C. It achieves higher speed by using fewer layers
- D. It uses a recurrent backbone instead of a CNN
Answer: B. It eliminates the need for NMS by using a transformer with set prediction
DETR treats detection as a direct set prediction problem using a transformer encoder-decoder, removing the need for handcrafted NMS.
Take the full CNN - Convolutional Neural Networks practice test
CNN Exam Flashcards: Quick Nephrology Nursing Facts
🧪 Who administers the CNN certification exam?
The Certified Nephrology Nurse (CNN) exam is administered by the Nephrology Nursing Certification Commission (NNCC). The NNCC is an independent, ANCC-accredited credentialing body affiliated with the American Nephrology Nurses Association (ANNA).
START CNN PRACTICE TEST📋 What are the CNN exam eligibility requirements?
To sit for the CNN exam you need a current, unrestricted RN license, a minimum of 2 years of RN experience, and at least 2,000 hours of nephrology nursing practice within the prior two years, plus 30 contact hours of approved nephrology continuing education.
START CNN PRACTICE TEST❓ How many questions are on the CNN exam?
The CNN examination contains 150 multiple-choice questions, of which 125 are scored and 25 are unscored pretest items. You are given three hours to complete the computer-based test at a Prometric testing center.
START CNN MCQ TEST✅ What is the passing score for the CNN exam?
The CNN exam uses a scaled score with a passing standard of 95 out of a possible 125 scored questions, set by criterion-referenced standard setting. Scores are reported as pass or fail, and candidates learn their result immediately after finishing.
START CNN MCQ TEST🩺 What topics does the CNN exam cover?
The CNN content outline covers hemodialysis, peritoneal dialysis, kidney transplantation, chronic kidney disease management, acute kidney injury, pharmacology, nutrition, fluid and electrolyte balance, and the psychosocial care of nephrology patients across the lifespan.
START CNN PRACTICE TEST🔁 How often do you have to renew CNN certification?
CNN certification is valid for three years. To recertify you must hold a current RN license and complete either 60 contact hours of approved continuing education plus required practice hours, or retake and pass the CNN examination before your credential expires.
START CNN TRIVIA TEST💰 How much does the CNN exam cost?
The CNN exam fee is set by the NNCC and is discounted for ANNA members. Candidates typically pay a lower member rate and a higher non-member rate, so joining ANNA before applying can offset part of the examination cost.
START CNN PRACTICE TEST⚖️ CNN vs CDN: what is the difference?
The CNN credential is for registered nurses in nephrology, while the Certified Dialysis Nurse (CDN) credential requires fewer practice hours and targets RNs focused specifically on dialysis. Both are offered by the NNCC, but CNN demands broader nephrology experience.
START CNN PRACTICE TEST💵 How much do certified nephrology nurses earn?
Nephrology nurses in the United States generally earn salaries in line with other experienced RNs, and certification can strengthen earning potential and promotion prospects. Pay varies by state, employer, and years of experience in dialysis or transplant settings.
START CNN TRIVIA TEST📚 How should you study for the CNN exam?
Effective CNN prep combines the ANNA Core Curriculum for Nephrology Nursing, the NNCC content outline, and timed practice questions. Focus on dialysis adequacy, lab value interpretation, and pharmacology, and use flashcards and practice tests to build recall under exam conditions.
START CNN MCQ TESTCNN Questions and Answers
Official Resources
- Nephrology Nursing Certification Commission (NNCC) — the official body that administers the CNN exam, publishes the content outline, and handles applications and recertification.
- American Nephrology Nurses Association (ANNA) — the professional association offering the Core Curriculum, continuing-education contact hours, and member discounts on the CNN examination.
- National Kidney Foundation (NKF) — authoritative clinical guidance on chronic kidney disease, dialysis, and transplantation that underpins much of the CNN exam content.
Sources & last verified
- Nephrology Nursing Certification Commission (NNCC), with C-NET (Center for Nursing Education and Testing) as test admini — number of questions, time limit, passing score (official source). “The CNN exam consists of 150 questions and must be completed in three (3) hours.” Verified Oct 25, 2026.
- Nephrology Nursing Certification Commission (NNCC), with C-NET (Center for Nursing Education and Testing) as test admini — exam fee, retake policy, validity, score release (official source). “$300 ANNA / NOVA / ASN / NKF Member ❏ $350 Non-member” Verified Oct 25, 2026.
How we verify: editorial & fact-checking policy. Report an error: contact us.
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