本番の試験会場で時間切れになってしまった、という声は珍しくありません。CertShikenのNCA-GENM模擬試験は実際の試験環境を再現しており、NVIDIA Generative AI Multimodalの制限時間や問題形式に慣れた状態で本番に臨めます。

NVIDIA NCA-GENM 試験概要:

認定ベンダー:	NVIDIA
試験名:	NVIDIA Generative AI Multimodal 認定試験 (NCA-GENM)
試験番号:	NCA-GENM
試験形式:	選択式, シナリオベース問題
出題数:	50-60
試験時間:	60 分
受験料:	$125 USD
対応言語:	英語
認定の有効期間:	2年間
関連資格:	NVIDIA Certified Associate: Generative AI LLMs (NCA-GENL)
推奨トレーニング:	NVIDIA Deep Learning Institute (DLI) コース
受験申し込み:	NVIDIA認定ポータル
サンプル問題:
受験方法:	オンライン監視付き試験（リモート）
前提条件:	ジェネレーティブAIおよび機械学習の概念に関する基本的な理解が推奨されます。Pythonおよびニューラルネットワークに関する知識があると役立ちます。
公式シラバスのURL:	https://www.nvidia.com/en-us/learn/certification/generative-ai-multimodal-associate/

NVIDIA NCA-GENM 試験シラバストピック:

NVIDIA Generative AI Multimodalに関するよくあるご質問

NVIDIA Generative AI Multimodal 認定 NCA-GENM 試験問題：

問題 #1

In ML applications, which machine learning algorithm is commonly used for creating new data based on existing data?

A. Decision tree
B. Generative adversarial network (GAN)
C. Support vector machine (SVM)
D. K-means clustering

問題 #2

What are some methods to overcome limited throughput between CPU and GPU?

A. Increase the number of CPU cores.
B. Using techniques like memory pooling.
C. Increase the clock speed of the CPU.
D. Upgrade the GPU to a higher-end model.

問題 #3

You are developing a ML model for image classification. You have a dataset with 10,000 images of cats, dogs and birds. Which of the following ML models would be the most appropriate choice for this task?

A. K-Means Clustering
B. Logistic Regression
C. Convolutional Neural Network (CNN)
D. Linear Regression

問題 #4

You want to evaluate the performance of an AI model. Which of the following is a method for AI model evaluation?

A. Calculating the model's accuracy from randomly selected data points from the dataset not used during the model's training.
B. Interviewing the developers of the AI model to assess its performance.
C. Randomly selecting data points from the training set and calculating the accuracy of the model on these data points.
D. Calculating the loss function of the model on the training set.

問題 #5

What does 'modality alignment' refer to?

A. The process of integrating diverse data types such as text, images, audio, time series, and geospatial information.
B. Addressing challenges related to missing or incomplete information across different modalities.
C. The integration of pretrained models to perform custom tasks involving different types of data.
D. Aligning different modalities within multimodal data to ensure meaningful connections and associations.

解説：