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NVIDIA NCA-GENL Exam Overview:
| Certification Vendor: | NVIDIA |
|---|---|
| Exam Name: | Generative AI LLMs Associate Certification Exam |
| Exam Number: | NCA-GENL |
| Passing Score: | Not officially published; typically approx. 70% |
| Certificate Validity Period: | 2 years |
| Exam Format: | Multiple-select, Multiple-choice, Single-answer |
| Real Exam Qty: | 50–60 |
| Related Certifications: | NVIDIA-Certified Professional: Generative AI LLMs (NCP-GENL) |
| Exam Price: | $125 USD |
| Exam Duration: | 60 minutes |
| Available Languages: | Chinese, English |
| Recommended Training: | NVIDIA Generative AI Training Courses |
| Exam Registration: | NVIDIA Certification Registration |
| Sample Questions: |  |
| Exam Way: | Online remote proctored exam |
| Pre Condition: | No formal prerequisites; recommended basic understanding of generative AI, large language models, and Python programming |
| Official Syllabus URL: | https://www.nvidia.com/en-us/learn/certification/generative-ai-llm-associate/ |
NVIDIA NCA-GENL Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Machine Learning and Neural Networks Fundamentals | 15% | - Neural network principles
|
| Prompt Engineering and Alignment | 20% | - Prompt design strategies
|
| Ethics, Safety and Best Practices | 10% | - Responsible AI
|
| NVIDIA Ecosystem and Tools | 15% | - Deployment and integration
|
| Large Language Models Architecture | 25% | - Transformer architecture
|
| Data Processing and Experimentation | 15% | - Experiment workflow
|
NCA-GENL Exam FAQ: What Candidates Ask About NVIDIA Generative AI LLMs
The NCA-GENL exam, officially known as NVIDIA Generative AI LLMs, is the NVIDIA test that leads to the NVIDIA-Certified Associate: Generative AI LLMs certification at the Associate level. Passing it validates the skills employers expect from a certified professional. It is also associated with related credentials such as NVIDIA-Certified Professional: Generative AI LLMs (NCP-GENL).
The NCA-GENL exam contains 50–60 questions, and you have 60 minutes to complete them. Work out your per-question pace before test day, and flag slow items instead of stalling on them — time pressure, not knowledge, sinks many first attempts. Timed mock exams in the Actual4Exams test engines are the most reliable way to build that rhythm.
The passing score for the NCA-GENL exam is Not officially published; typically approx. 70%, and the official registration fee is $125 USD. If you miss the mark, a retake means paying the full fee again, so book your seat only when you are ready. A practical benchmark: score consistently above the passing line on timed practice tests before scheduling the real exam.
No formal prerequisites; recommended basic understanding of generative AI, large language models, and Python programming
Entry requirements can change, so confirm the latest conditions on the official exam page: https://www.nvidia.com/en-us/learn/certification/generative-ai-llm-associate/.
You can book the NCA-GENL exam through the official registration channels below:
Exam delivery: Online remote proctored exam. Seats at popular test centers fill quickly, so schedule early once your preparation is on track.
NVIDIA recommends the following training options for NVIDIA Generative AI LLMs candidates:
Pair any course with the 97 practice questions from Actual4Exams to measure how ready you really are before paying the exam fee.
Yes. A free PDF demo of the NVIDIA Generative AI LLMs questions is available, so you can check the question style and answer quality before you pay. Every purchase also includes 365 days of free updates, and if the product expires you can renew the update service at a 50% discount from your member zone.
If you take the corresponding NCA-GENL exam within 60 days of purchase and do not pass, you can apply for a full refund under the 100% Money Back Guarantee: submit a scan of your enrollment slip and your official Score Report (PDF) within 2 days of the exam date, and the claim is processed within 7 days. Attempts made within 3 days of purchase, downloads without an actual exam attempt, free materials, and expired orders are not eligible, and the candidate name must match the payer name. Prefer new material instead of a refund? You can exchange your purchase for two free products of equal value and keep the update service on your original product. As for delivery, the files are available for instant download and are also emailed to you within one minute of payment — if nothing arrives within 2 hours, contact customer service. There is no limit on how many computers you can install the product on.
The official NVIDIA Generative AI LLMs outline is organized into 6 domains. The first three are:
- NVIDIA Ecosystem and Tools — 15% of the exam
- Machine Learning and Neural Networks Fundamentals — 15% of the exam
- Prompt Engineering and Alignment — 20% of the exam
See the complete exam topics section above for the full outline and the weighting of every domain.
NVIDIA Generative AI LLMs Sample Questions:
Question 1
In the context of language models, what does an autoregressive model predict?
A. The next token solely using recurrent network or LSTM cells.
B. The probability of the next token in a text given the previous tokens.
C. The probability of the next token by looking at the previous and future input tokens.
D. The probability of the next token using a Monte Carlo sampling of past tokens.
Question 2
You are using RAPIDS and Python for a data analysis project. Which pair of statements best explains how RAPIDS accelerates data science?
A. RAPIDS is a Python library that provides functions to accelerate the PCIe bus throughput via word- doubling.
B. RAPIDS enables on-GPU processing of computationally expensive calculations and minimizes CPU- GPU memory transfers.
C. RAPIDS provides lossless compression of CPU-GPU memory transfers to speed up data analysis.
Question 3
In the context of developing an AI application using NVIDIA's NGC containers, how does the use of containerized environments enhance the reproducibility of LLM training and deployment workflows?
A. Containers reduce the model's memory footprint by compressing the neural network.
B. Containers encapsulate dependencies and configurations, ensuring consistent execution across systems.
C. Containers enable direct access to GPU hardware without driver installation.
D. Containers automatically optimize the model's hyperparameters for better performance.
Question 4
What are the main advantages of instructed large language models over traditional, small language models (<
300M parameters)? (Pick the 2 correct responses)
A. Cheaper computational costs during inference.
B. Trained without the need for labeled data.
C. It is easier to explain the predictions.
D. Single generic model can do more than one task.
E. Smaller latency, higher throughput.
Question 5
When comparing and contrasting the ReLU and sigmoid activation functions, which statement is true?
A. ReLU and sigmoid both have a range of 0 to 1.
B. ReLU is more computationally efficient, but sigmoid is better for predicting probabilities.
C. ReLU is less computationally efficient than sigmoid, but it is more accurate than sigmoid.
D. ReLU is a linear function while sigmoid is non-linear.
Solutions:
| Question 1 Answer: B | Question 2 Answer: B | Question 3 Answer: B | Question 4 Answer: A,D | Question 5 Answer: B |
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