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AWS Certified AI Practitioner practice questions

218 free questions with answers and explanations.

Practice test
  1. 151.A team is developing a generative AI model to create realistic marketing campaign texts. The initial models produce grammatically correct but often repetitive and uninspired content. To improve the diversity and creativity of the generated text, which parameter adjustment is most likely to yield better results?AI/ML and Generative AI Fundamentals
  2. 152.An e-commerce company wants to implement a system that suggests products to customers based on their past purchases and browsing history. The goal is to increase sales by showing highly relevant items. Which type of machine learning task is this system performing?AI/ML and Generative AI Fundamentals
  3. 153.A research team is developing a generative AI model to create novel protein structures based on a sequence of amino acids. They want the generated structures to maintain realistic physical properties and chemical bonds. While the model can generate diverse structures, it sometimes produces outputs that are chemically impossible or unstable. What core concept of generative AI is the team struggling to ensure in their model's output?AI/ML and Generative AI Fundamentals
  4. 154.A research team is developing a generative AI model to create novel protein structures based on known amino acid sequences. They need a model architecture that excels at understanding and generating complex sequential data with long-range dependencies. Which of the following generative AI model types would be most suitable for this task?AI/ML and Generative AI Fundamentals
  5. 155.A data scientist is building an AI/ML model to predict customer churn. The dataset includes a 'Subscription Tier' feature with values like 'Basic', 'Premium', and 'Enterprise'. To prepare this categorical feature for a machine learning algorithm, which technique is most appropriate if the model assumes numerical input and there is no inherent order among the tiers?AI/ML and Generative AI Fundamentals
  6. 156.A machine learning engineer is developing a generative AI model to create new musical compositions. They want to control the level of randomness or creativity in the generated music. Specifically, they want to be able to make the model produce either highly predictable, structured compositions or more experimental, surprising pieces. Which parameter is typically adjusted in generative models to achieve this control over output randomness?AI/ML and Generative AI Fundamentals
  7. 157.A machine learning engineer is deploying a model that classifies customer support tickets by issue type. The model achieves 98% accuracy on the training data but only 65% accuracy on new, unseen customer tickets. What is the most likely issue with this model?AI/ML and Generative AI Fundamentals
  8. 158.A data scientist is preparing a dataset of customer reviews for sentiment analysis using a generative AI model. The model needs to understand the semantic relationships between words, such as 'good' being closer to 'excellent' than to 'terrible'. Which data representation technique should be used to capture these semantic relationships?AI/ML and Generative AI Fundamentals
  9. 159.A research team is developing a generative AI model to create novel protein structures based on specific functional requirements. The model needs to understand complex relationships between amino acid sequences and their resulting 3D structures, and critically, how changes in one part of the sequence can influence distant parts of the structure. Which neural network architecture is best suited for handling these long-range dependencies and intricate pattern recognition in sequential data for generative tasks?AI/ML and Generative AI Fundamentals
  10. 160.A healthcare provider is deploying an AI-powered diagnostic tool. During testing, it's discovered that the tool performs significantly worse for certain demographic groups compared to others, even though the overall accuracy seems acceptable. This discrepancy is likely due to which of the following issues?AI/ML and Generative AI Fundamentals
  11. 161.A data scientist is preparing a dataset for an image classification task where the goal is to identify different species of birds from photographs. Each image in the dataset is associated with a specific bird species, such as 'Bald Eagle', 'Cardinal', or 'Blue Jay'. Which key AI/ML concept defines these specific bird species labels that the model will learn to predict?AI/ML and Generative AI Fundamentals
  12. 162.A data engineer is preparing a dataset for an AI/ML model that will predict whether a customer will renew their subscription. The dataset contains a unique 'CustomerID' for each record. If this feature is directly included in the model training, it could lead to the model memorizing individual customer details rather than learning general patterns, potentially resulting in poor generalization. Which feature engineering technique should be applied to address this issue?AI/ML and Generative AI Fundamentals
  13. 163.A data scientist is working with a large text corpus to train a generative AI model. They need to prepare the text data to be suitable for machine learning algorithms, which typically require numerical input. Which of the following techniques would be most appropriate for converting words into numerical representations while capturing semantic meaning?AI/ML and Generative AI Fundamentals
  14. 164.A financial institution is implementing a machine learning model to detect fraudulent transactions. The model is trained on historical data where only a very small percentage of transactions are actually fraudulent. During evaluation, the model achieves 99.9% accuracy. However, a review by human experts reveals that many actual fraudulent transactions are still being missed. Which evaluation metric should the team prioritize to address this issue?AI/ML and Generative AI Fundamentals
  15. 165.An AI/ML team has developed a large language model (LLM) and deployed it for customer service. After initial deployment, they notice that the model sometimes produces responses that are factually incorrect or 'hallucinates' information not present in its training data. Which concept describes this unwanted behavior in generative AI models?AI/ML and Generative AI Fundamentals
  16. 166.A research team is developing a generative AI model to create novel protein structures based on specific functional requirements. They want the model to understand the long-range dependencies within protein sequences and how changes in one part of the sequence can affect distant parts. Which neural network architecture is best suited for this task?AI/ML and Generative AI Fundamentals
  17. 167.A data scientist is preparing a dataset for an AI/ML model that will predict customer churn. One of the features is 'Subscription Type', which can be 'Basic', 'Premium', or 'Enterprise'. Which of the following data preprocessing techniques is most appropriate for this categorical feature if the model expects numerical input and there is no inherent order among the subscription types?AI/ML and Generative AI Fundamentals
  18. 168.A retail company wants to analyze customer reviews to automatically categorize them as positive, negative, or neutral. Which type of machine learning task is most appropriate for this requirement?AI/ML and Generative AI Fundamentals
  19. 169.A data scientist is preparing a dataset for an AI/ML model that will predict customer churn. The dataset contains a 'Customer ID' column, which is a unique identifier for each customer. Which of the following best describes the appropriate action for this column in the context of model training?AI/ML and Generative AI Fundamentals
  20. 170.A software company is developing an AI-powered chatbot for customer service. The chatbot needs to understand user queries and provide relevant responses. To improve the chatbot's ability to maintain context and understand the relationships between words in a long conversation, which AI concept is most directly relevant?AI/ML and Generative AI Fundamentals
  21. 171.A team is developing a large language model (LLM) for a specific medical domain, such as generating diagnostic summaries from patient notes. They have access to a large general-purpose LLM already trained on a vast amount of text. To adapt this general LLM to the medical domain effectively, which technique is most appropriate for leveraging the pre-trained knowledge while specializing it?AI/ML and Generative AI Fundamentals
  22. 172.A financial institution is implementing a machine learning model to detect fraudulent transactions. The model is designed to flag suspicious activities, and the primary concern is to minimize the number of actual fraudulent transactions that are missed. Which evaluation metric should the institution prioritize to ensure this objective is met?AI/ML and Generative AI Fundamentals
  23. 173.A social media platform is developing a generative AI model to create personalized short video clips for users based on their interests and trending topics. To achieve high-quality, relevant video generation, the model needs to understand which parts of the input text description (e.g., 'sunset beach with surfing dog') are most important when generating specific elements of the video (e.g., the background, the subject). Which mechanism is crucial for enabling the model to focus on relevant parts of the input sequence?AI/ML and Generative AI Fundamentals
  24. 174.A healthcare provider is deploying an AI-powered diagnostic tool. During testing, it's discovered that the tool performs significantly worse for patients from a specific demographic group, leading to delayed or incorrect diagnoses for them, while performing well for the majority of other patients. Which ethical concern in AI/ML does this situation highlight?AI/ML and Generative AI Fundamentals
  25. 175.A data scientist is investigating a trained AI model that predicts loan default risk. They discover that the model consistently assigns higher default probabilities to applicants from a specific zip code, even when other financial indicators are similar to applicants from other areas. This behavior leads to a disproportionately high rejection rate for individuals from that zip code. Which key AI/ML concept does this scenario most directly illustrate?AI/ML and Generative AI Fundamentals
  26. 176.A team is developing a large language model (LLM) for a specialized legal domain, such as patent law. They want to leverage a pre-trained general-purpose LLM but adapt it to understand and generate text specific to legal terminology, case precedents, and filing procedures. What is the most effective technique to achieve this adaptation without training a new model from scratch?AI/ML and Generative AI Fundamentals
  27. 177.A data scientist is preparing a dataset for an AI/ML model that will predict the probability of a customer clicking on an advertisement. The dataset contains various numerical features, such as 'Age', 'Income', and 'Number of Past Clicks'. These features have widely different scales and distributions. To prevent features with larger values from dominating the learning process, which data preprocessing technique should be applied?AI/ML and Generative AI Fundamentals
  28. 178.A team is developing a generative AI model to create new musical compositions. They want to control the 'creativity' or 'randomness' of the generated music, specifically how much the model deviates from its learned patterns when generating new sequences. Which parameter should they adjust to achieve this control?AI/ML and Generative AI Fundamentals
  29. 179.A data scientist is evaluating the performance of a binary classification model that predicts fraud. The model has a high number of false positives, meaning many legitimate transactions are flagged as fraudulent. Which metric should the data scientist focus on to reduce these false positives without significantly missing actual fraudulent cases?AI/ML and Generative AI Fundamentals
  30. 180.An e-commerce company wants to use machine learning to recommend products to customers. They have a vast amount of historical purchase data, including customer IDs, product IDs, and ratings. Which type of machine learning task is most appropriate for building a product recommendation system based on this data?AI/ML and Generative AI Fundamentals
  31. 181.A team is developing a new generative AI model to compose entire musical pieces. They are exploring different approaches for the 'inference' stage, where the trained model actually generates new music. Which of the following best describes the primary goal of the inference stage in this context?AI/ML and Generative AI Fundamentals
  32. 182.An AI/ML team is developing a new model and has just completed the data preparation phase. According to the standard machine learning lifecycle, what is the immediate next step?AI/ML and Generative AI Fundamentals
  33. 183.A data scientist is investigating a trained AI model that predicts loan default risk. They discover that the model consistently predicts a higher default risk for applicants from a particular zip code, even when controlling for other financial factors. This leads to a disproportionately higher rate of loan rejections for residents of that zip code. What type of issue does this scenario represent?AI/ML and Generative AI Fundamentals
  34. 184.A satellite imaging company uses an AI/ML model to classify land use from aerial photographs (e.g., forest, urban, agricultural). Each photograph is labeled with one of these categories. Once the model is trained, it processes new, unlabeled photographs to assign them to a land-use category. In the context of the machine learning lifecycle, what is this final step of assigning categories to new data called?AI/ML and Generative AI Fundamentals
  35. 185.A developer is creating a conversational AI agent that needs to maintain context over a prolonged dialogue with a user. The agent should be able to refer back to previous turns in the conversation to provide coherent and relevant responses. Which generative AI technique is most fundamental for enabling this long-range dependency and contextual understanding in dialogue systems?AI/ML and Generative AI Fundamentals
  36. 186.A developer is building a large language model (LLM) for a specialized legal domain. They have a pre-trained general-purpose LLM and a smaller, highly relevant dataset of legal documents. To adapt the LLM effectively to the legal domain without training from scratch, which technique should they employ?AI/ML and Generative AI Fundamentals
  37. 187.A team is developing a new generative AI model to compose entire musical pieces. They are currently in the stage where the trained model is being used to produce new, original compositions based on a given prompt or style. What stage of the AI/ML lifecycle does this activity represent?AI/ML and Generative AI Fundamentals
  38. 188.A machine learning engineer is developing a generative AI model to create new musical compositions. The model is currently producing compositions that are largely repetitive and lack creativity, often repeating the same short melodic phrases. Which of the following generative AI concepts is most directly related to improving the diversity and novelty of the generated output?AI/ML and Generative AI Fundamentals
  39. 189.A financial institution is implementing a machine learning model to detect fraudulent transactions. The model is designed to flag suspicious activities, and the primary concern is to minimize the number of legitimate transactions that are incorrectly flagged as fraudulent, as this can lead to customer dissatisfaction and operational overhead. Which evaluation metric should the institution prioritize to ensure this objective is met?AI/ML and Generative AI Fundamentals
  40. 190.A team is developing a new generative AI model to compose entire musical pieces. They are now in the phase where the trained model is used to actually create novel compositions based on input prompts. Which stage of the machine learning lifecycle does this activity represent?AI/ML and Generative AI Fundamentals
  41. 191.A startup is developing an AI-powered system to generate marketing copy for various products. They want the system to produce unique and compelling text for each product without being explicitly programmed with rules for every possible product type. Which core characteristic of generative AI makes this possible?AI/ML and Generative AI Fundamentals
  42. 192.A machine learning engineer is evaluating a model designed to identify rare fraudulent transactions. The model correctly identifies 90 out of 100 actual fraudulent transactions but also flags 50 legitimate transactions as fraudulent. There are 10,000 total legitimate transactions. What is the False Positive Rate (FPR) for this model?AI/ML and Generative AI Fundamentals
  43. 193.A pharmaceutical company is developing a foundation model to accelerate drug discovery by predicting molecular interactions and synthesizing novel chemical structures. The model needs to perform highly specialized reasoning, infer complex relationships from sparse biological data, and generate new compounds that adhere to specific chemical rules. Which foundation model characteristic is most critical for achieving these advanced capabilities?Foundation Models
  44. 194.A research institution is developing a new scientific discovery platform that integrates data from various modalities, including academic papers (text), experimental results (structured data), microscopic images, and chemical compound structures. They need a foundation model that can process and reason across all these different data types to identify novel correlations and hypotheses. Which foundation model type is best suited for this requirement?Foundation Models
  45. 195.A social media platform is developing a generative AI model to create personalized short video clips for users based on their preferences and trending topics. For the model to effectively combine visual elements, audio segments, and text overlays in a coherent and contextually relevant manner, it needs a mechanism to prioritize and relate different parts of the input data. Which AI mechanism is crucial for this capability?AI/ML and Generative AI Fundamentals
  46. 196.A team of researchers is training a new, very large foundation model with billions of parameters on a massive, diverse dataset. During the training process, they observe that the model's performance on the training data is exceptionally high, achieving near-perfect scores. However, when evaluated on a separate, unseen validation dataset, the model's performance is significantly worse. This discrepancy indicates which common issue in machine learning?Foundation Models
  47. 197.A data scientist is preparing a dataset for an AI/ML model that will predict the probability of a customer defaulting on a loan. The dataset contains various numerical features such as 'LoanAmount' (ranging from $1,000 to $1,000,000) and 'CreditScore' (ranging from 300 to 850). What data preprocessing technique should be applied to these features to ensure that features with larger numerical ranges do not disproportionately influence the model?AI/ML and Generative AI Fundamentals
  48. 198.An e-commerce company wants to implement a system that suggests products to customers based on their past purchases, browsing history, and similar users' behavior. The primary goal is to increase customer engagement and sales by showing relevant items. Which machine learning task best describes the core functionality of this system?AI/ML and Generative AI Fundamentals
  49. 199.A data scientist is preparing a dataset of customer reviews for sentiment analysis using a generative AI model. They need to represent each word in the reviews as a numerical vector that captures its semantic meaning and contextual relationships with other words. Which technique is best suited for this purpose?AI/ML and Generative AI Fundamentals
  50. 200.A financial institution is implementing a machine learning model to detect fraudulent transactions. They are particularly concerned about missing actual fraudulent transactions, even if it means flagging some legitimate transactions incorrectly. Which metric should they prioritize to evaluate the model's effectiveness?AI/ML and Generative AI Fundamentals