AWS Certified AI Practitioner AIF-C01 Exam Study Guide

A collection of flashcards based on key concepts and information covered in the AWS Certified AI Practitioner AIF-C01 exam study guide.

What is the primary focus of artificial intelligence (AI)?

AI focuses on creating systems capable of performing intelligent tasks that mimic human intelligence.

What is machine learning (ML)?

ML is a subset of AI that allows algorithms to learn patterns from data and improve performance over time without explicit programming.

What is deep learning (DL)?

DL is a specialized subset of ML that uses artificial neural networks to model complex patterns in large datasets.

What is the difference between supervised and unsupervised learning?

Supervised learning uses labeled datasets to train models, while unsupervised learning works with unlabeled data to find patterns or groupings.

What is overfitting?

Overfitting occurs when a model performs well on training data but poorly on unseen data due to being too complex.

What is the purpose of the activation function in a neural network?

The activation function determines whether a neuron should be activated based on its input, introducing non-linearity into the model.

What is the gradient descent algorithm used for?

Gradient descent is used to optimize a model by minimizing the loss function through iterative updates of the model parameters.

What are weight and bias in the context of neural networks?

Weights are parameters that influence the strength of the signal from one neuron to another, while biases allow neurons to act regardless of the input.

Name two common types of neural network architectures.

Feedforward Neural Networks (FNN) and Convolutional Neural Networks (CNN).

What is the purpose of regularization in machine learning?

Regularization is used to prevent overfitting by adding a penalty for complexity to the loss function.

What is the difference between a feedforward neural network and a recurrent neural network?

Feedforward neural networks process inputs in one direction, while recurrent neural networks have connections that allow cycles, making them suitable for sequence data.

What are generative adversarial networks (GAN)?

GANs are a type of neural network architecture that consist of two competing networks (generator and discriminator) to create new, synthetic instances of data.

What is transfer learning?

Transfer learning is a technique where a pre-trained model is adapted for a new, related task, saving time and resources.

What is the primary function of Amazon Rekognition?

Amazon Rekognition is used for image and video analysis, detecting objects, faces, and inappropriate content.

What AWS service can be used for natural language processing tasks?

Amazon Comprehend is an AWS service designed for natural language processing, capable of extracting insights and understanding text.

What does the term 'embedding' refer to in machine learning?

Embeddings are dense vector representations of data used to capture semantic meanings and relationships.

What metrics can be used for evaluating the performance of classification models?

Common metrics include accuracy, precision, recall, and F1 score.

How is the scoring system for the AWS Certified AI Practitioner exam structured?

The exam uses a scaled scoring model from 100 to 1000, with a minimum passing score of 700.

What advantages does Amazon SageMaker provide for machine learning?

Amazon SageMaker offers tools for building, training, and deploying machine learning models, simplifying the ML workflow.

Why is data normalization important in machine learning?

Normalization standardizes data, allowing models to learn more effectively and improving convergence speed.

What is the purpose of feature engineering?

Feature engineering is the process of selecting, transforming, and creating new variables to improve model performance.

What is the role of a hyperparameter in machine learning?

Hyperparameters are parameters that are set before the learning process begins and are crucial in determining the structure and performance of models.

What is the importance of ensuring data quality in AI models?

High-quality data is essential for accurate predictions; poor data quality can lead to unreliable models and misinformation.

What does Amazon Kendra provide as a service?

Amazon Kendra is an intelligent search service that utilizes machine learning to deliver accurate search results across multiple data sources.

What precautions are necessary to mitigate risks in AI models?

Implementing regular audits, establishing data governance, and using ethical frameworks to monitor performance are crucial for risk mitigation.

What is the significance of the AWS shared responsibility model?

The shared responsibility model delineates security responsibilities between AWS and the customer, ensuring that both parties understand their roles.

What is the key advantage of using Amazon Bedrock for generative AI applications?

Amazon Bedrock provides access to a variety of foundation models and tools for creating scalable, secure generative AI applications.

How does the Amazon SageMaker Model Monitor function?

It continuously monitors ML models deployed in production to detect data drift, bias, and errors.

What is retrieval augmented generation (RAG)?

RAG combines information retrieval techniques with generative models to improve the accuracy and relevance of outputs by using real-time retrieved data.

What is the function of Amazon Transcribe?

Amazon Transcribe is an automatic speech recognition service that converts speech into text in real-time.

How does Amazon Polly enhance applications?

Amazon Polly converts text into lifelike speech, enabling applications to utilize voice responses for better user interaction.

Why is it important to have transparency in AI systems?

Transparency helps build trust and accountability in AI decisions by allowing users to understand how models generate outcomes.

What are the ethical implications of AI technology?

Ethical implications involve biases, accountability, transparency, and ensuring that AI systems are used responsibly and legally.

What should organizations consider from an ethical perspective when deploying AI?

Organizations should evaluate potential biases, data ethics, compliance with laws, and the impact of their AI systems on society.

What is the primary function of Amazon SageMaker Canvas?

SageMaker Canvas allows users to build machine learning models using a no-code interface, making ML accessible to non-experts.

What benefits does prompt engineering provide to AI models?

Prompt engineering improves the quality and relevance of AI-generated responses by guiding models with structured inputs.

How do human evaluations contribute to assessing AI models?

Human evaluations provide qualitative insights that quantitative metrics may miss, enhancing understanding of model performance in context.

What factors influence the costs associated with deploying foundation models?

Factors include compute resources, operational expenses, training duration, and licensing fees.

How can organizations ensure compliance with regulations using AWS?

By utilizing AWS tools such as AWS Artifact for compliance reports and AWS IAM for access management.

What is the objective of using Guardrails in AI applications?

To establish safety measures that prevent the generation of harmful or unwanted content by AI systems.

Why is it necessary to monitor the performance of AI models continuously?

Continuous monitoring helps detect issues like data drift or bias, ensuring the model remains effective and reliable over time.

What are the typical data formats used in machine learning?

Structured, semi-structured, and unstructured data formats are commonly utilized in machine learning applications.

What is human feedback in reinforcement learning?

Human feedback is used to guide the model’s learning process, improving its predictions and performance with human insight.

What is the role of AWS Lambda in data processing for AI models?

AWS Lambda allows serverless computing to manage backend operations for data processing without needing to manage servers.

How is Amazon Textract utilized in AI applications?

Amazon Textract automatically extracts text and structured data from documents, providing businesses with scalable document processing capabilities.

What does the term 'bias' refer to in the context of AI?

Bias refers to unfair treatment or results generated by AI systems, often stemming from the data used for training.

What safeguards can be put in place to prevent prompt injection attacks?

Implementing input validation, sanitation techniques, and monitoring can help prevent prompt injection attacks.

What is the impact of training data on machine learning models?

Training data significantly affects model accuracy and performance; high-quality data leads to better predictive capabilities.

What services does AWS provide to help with ethical AI use?

AWS offers services like Amazon SageMaker Clarify for monitoring bias and ensuring transparency in AI models.

How does Amazon Fraud Detector function?

Amazon Fraud Detector uses machine learning to identify potentially fraudulent online activities by analyzing transaction data.

What is the importance of deploying AI models in a cloud environment?

Deploying AI models in a cloud environment provides scalability, cost-effectiveness, and access to powerful resources.

What is the benefit of using ensemble learning in AI?

Ensemble learning improves model performance by combining predictions from multiple models, leading to more accurate results.

How can bias be mitigated in AI systems?

Bias can be mitigated through diverse data representation, regular audits, and implementing fairness protocols in model training.

What considerations are essential for selecting an appropriate AI service on AWS?

Considerations should include cost, modality requirements, latency, and the specific use case of the service.

How does compliance impact the deployment of AI solutions?

Compliance ensures adherence to legal standards and promotes user trust, requiring organizations to align AI applications with relevant regulations.

What is the financial impact of operationalizing AI models?

Operationalizing AI models can involve significant costs due to infrastructure, maintenance, and the need for skilled personnel.

What is the significance of transparency and accountability in AI development?

Transparency and accountability in AI development foster user trust, ensure adherence to ethical standards, and allow stakeholders to understand AI decisions.

What role does continuous learning play in the adaptability of AI models?

Continuous learning allows AI models to remain relevant by adapting to new information and patterns over time, ensuring accuracy and effectiveness.

What is Amazon SageMaker Ground Truth used for?

Amazon SageMaker Ground Truth provides tools for creating high-quality labeled datasets by combining human labeling and machine learning.

What is the objective of deploying machine learning models on AWS?

The goal is to leverage AWS's infrastructure for efficient scaling, management, and secure deployment of machine learning models.

How do ethical considerations shape the development of AI solutions?

Ethical considerations guide the responsible use of AI, ensuring that models are fair, transparent, and accountable to users and society.

What is the expected outcome of utilizing retrieval augmented generation systems?

RAG systems improve the relevance and accuracy of model outputs by integrating real-time data retrieval with generative responses.

What tools can be used to ensure model fairness?

Tools such as Amazon SageMaker Clarify help evaluate and ensure fairness in AI models during the model training process.