Hands-On with GenAI Tools and Technologies Exam Questions and Answers

Hands-On with GenAI Tools and Technologies certification exam assessment practice question and answer (Q&A) dump including multiple choice questions (MCQ) and objective type questions, with detail explanation and reference available free, helpful to pass the Hands-On with GenAI Tools and Technologies exam and earn Hands-On with GenAI Tools and Technologies certificate.

Question 1

Which of the following is not an example of how Generative AI can be used?

A. Creating images, music, or videos
B. Simulating conversation with users through rule-based logic
C. Improving customer interactions via a chatbot
D. Writing essays or summarizing text

Answer

B. Simulating conversation with users through rule-based logic

Explanation

While traditional chatbots use rule-based logic, this is not a generative AI capability. GenAI relies on learning patterns from data rather than fixed rules.

Question 2

What is a key focus of Industry 5.0, and how does Generative AI contribute to it?

A. Industry 5.0 centers on automation alone, and GenAI mainly replaces human labor in factories.
B. Industry 5.0 emphasizes human-machine collaboration and personalization, with GenAI supporting efficiency and innovation.
C. Industry 5.0 focuses solely on environmental sustainability, and GenAI helps reduce power usage in manufacturing.
D. Industry 5.0 aims to eliminate human involvement, with GenAI fully automating all industrial processes.

Answer

B. Industry 5.0 emphasizes human-machine collaboration and personalization, with GenAI supporting efficiency and innovation.

Explanation

A key focus of Industry 5.0 is the integration of human creativity and ingenuity with advanced technologies like AI and robotics to create a more sustainable, efficient, and personalized manufacturing process

Question 3

Which of the following is identified as a potential risk of using generative AI?

A. High energy consumption during model training
B. The tendency of models to generate false but plausible information
C. Difficulty in collecting enough training data
D. Poor user interface design in AI applications

Answer

B. The tendency of models to generate false but plausible information

Explanation

This is described as “hallucination,” where AI produces misleading or incorrect content that appears factual.

Question 4

In the context of Large Language Models (LLMs), what are “parameters”?

A. The topics an LLM is trained to talk about
B. The external data sources the model can access
C. The internal settings that influence how the model processes and generates text
D. The number of users interacting with the model at once

Answer

C. The internal settings that influence how the model processes and generates text

Explanation

Parameters are like control knobs that determine how the model understands patterns and produces responses.

Question 5

What is one of the primary benefits of effective prompt engineering for AI models?

A. It reduces the need for human input in the training process.
B. It enhances model accuracy by providing clear instructions and context.
C. It increases the complexity of AI models.
D. It encourages the AI to generate content that is irrelevant to the user’s goals.

Answer

B. It enhances model accuracy by providing clear instructions and context.

Explanation

Clear and well-structured prompts ensure that the AI produces more accurate and relevant responses by providing necessary context and instructions.

Question 6

What is the main challenge associated with prompt engineering for generative AI models?

A. Ensuring that AI models can perform a wide variety of tasks without detailed instructions.
B. Designing prompts that require no trial and error to generate the desired results.
C. Guiding AI models towards producing precise and relevant outputs, often requiring significant trial and error.
D. Automating the prompt creation process without human input.

Answer

C. Guiding AI models towards producing precise and relevant outputs, often requiring significant trial and error.

Explanation

Prompt engineering involves creating the right instructions to steer AI models in the desired direction, and this process can take several iterations to get right.

Question 7

What does the “Transformer” in GPT refer to?

A. A type of algorithm used only for image generation
B. A neural network architecture that helps understand word relationships in text
C. A method for translating text into different languages
D. A tool for transforming data into structured formats

Answer

B. A neural network architecture that helps understand word relationships in text

Explanation

The “Transformer” is a neural network design especially good at modeling the relationships between words, even when they’re far apart in a sentence.

Question 8

What is the primary reason you need to be cautious about sharing information with AI platforms?

A. AI platforms are designed to use all data for training, which can improve the system.
B. Sharing sensitive information, like your address or credit card details, with AI platforms can lead to privacy breaches.
C. AI platforms never use data for training purposes, so you can freely share sensitive information.
D. AI platforms only store data temporarily, and it doesn’t have any lasting impact.

Answer

B. Sharing sensitive information, like your address or credit card details, with AI platforms can lead to privacy breaches.

Explanation

It’s important to avoid sharing sensitive data, such as addresses or credit card details, with AI platforms to prevent privacy risks.

Question 9

Which of the following is a key source of training data for Generative AI models?

A. Only publicly available datasets like books and scientific journals.
B. Web scraping and crawling, public datasets, crowdsourcing, existing customer data, and user-generated content.
C. Only customer data, such as purchase history and call logs, are used to train GenAI models.
D. GenAI models exclusively use user-generated content from social media as their training data.

Answer

B. Web scraping and crawling, public datasets, crowdsourcing, existing customer data, and user-generated content.

Explanation

GenAI models draw data from multiple sources, including web scraping, public datasets, crowdsourcing, and more.

Question 10

What is DeepSeek primarily known for?

A. Creating entertainment-focused AI tools
B. Developing powerful and cost-effective large language models
C. Building robotics for industrial automation
D. Offering cloud storage solutions for AI data

Answer

B. Developing powerful and cost-effective large language models

Explanation

DeepSeek is known for building efficient, powerful, and affordable language models, especially for coding and reasoning tasks.

Question 11

What is the primary advantage of fine-tuning a pre-trained Generative AI model?

A. It requires starting the training process from scratch, allowing for greater control over the model’s capabilities.
B. It significantly reduces the amount of labeled data needed for training, making it cost-effective and efficient for specialized tasks.
C. It is not suitable for tasks with scarce or expensive data, as fine-tuning still requires large datasets.
D. It only works for natural language processing and cannot be applied to image recognition or other tasks.

Answer

B. It significantly reduces the amount of labeled data needed for training, making it cost-effective and efficient for specialized tasks.

Explanation

Fine-tuning leverages existing pre-trained models, reducing the need for extensive data and making the process more efficient.

Question 12

What distinguishes GPT-4 from earlier versions of GPT

A. It only processes text-based content and cannot handle images.
B. It is primarily focused on coding tasks, with no ability to analyze visual content.
C. It has the ability to interpret both text and visual content, such as images, diagrams, and infographics.
D. It is slower and more expensive to operate than previous models.

Answer

C. It has the ability to interpret both text and visual content, such as images, diagrams, and infographics.

Explanation

This is the defining feature of GPT-4, enabling it to handle multimodal data (text and images).

Question 13

Which of the following is NOT a recommended property of a good prompt?

A. Use clear and concise language without unnecessary technical terms.
B. Include only relevant information to avoid generating irrelevant outputs.
C. Introduce new topics to ensure the AI model explores a wider range of ideas.
D. Define technical terms if they are necessary to avoid ambiguity.

Answer

C. Introduce new topics to ensure the AI model explores a wider range of ideas.

Explanation

A good prompt should stay focused on the specific topic at hand. Introducing new topics can confuse the model and generate irrelevant responses.

Question 14

What is a key difference between traditional Machine Learning models and Generative AI models?

A. Traditional ML models rely on pre-trained models, while GenAI models require custom data collection and long training periods.
B. GenAI models use pre-trained models, which saves time and resources compared to traditional ML models that require custom model building and long training periods.
C. Traditional ML models do not require large datasets, while GenAI models do.
D. Both traditional ML models and GenAI models require the same amount of time and resources to train and maintain.

Answer

B. GenAI models use pre-trained models, which saves time and resources compared to traditional ML models that require custom model building and long training periods.

Explanation

GenAI models are more efficient, using pre-trained models to save time and resources for specific tasks.

Question 15

Which of the following is a direct consequence of ChatGPT’s limitations in understanding context and accuracy?

A. It consistently generates creative and novel solutions to problems.
B. It may produce answers that sound plausible but are factually incorrect or misleading.
C. It eliminates the need for human input in decision-making processes.
D. It guarantees unbiased answers, regardless of the dataset used.

Answer

B. It may produce answers that sound plausible but are factually incorrect or misleading.

Explanation

This is a direct consequence of the model’s inability to fully grasp context or intent, leading to responses that may sound accurate but are not reliable.