Prepare for the AIF-C01 AWS Certified AI Practitioner Exam

Free AIF-C01 Practice Questions (With Answers)

5 real questions from the AIF-C01 bank, with the full explanation for each answer. No sign-up needed to read them.

1. Question 1Fundamentals of AI and ML [Supervised, Unsupervised, and Reinforcement Learning]

   A data scientist is building a model to predict the exact price of a house based on features like its size, number of bedrooms, and location. The model is trained on a historical dataset of houses with known prices. What type of machine learning problem is this?

   • A.Reinforcement
   • B.Classification
   • C.Clustering
   • D.Regression
   Show answer and explanation

   Correct answer: D

   Correct. Regression is a supervised learning technique used to predict a continuous numerical output. Since the goal is to predict an exact price (a continuous value), this is a classic regression problem.

   Why the other options are wrong

   A. Incorrect. Reinforcement learning involves an agent learning to make decisions by interacting with an environment to maximize rewards. This problem involves learning from a static, labeled dataset.

   B. Incorrect. Classification is a supervised learning technique used to predict a discrete category or class label (e.g., 'spam' or 'not spam'), not a continuous numerical value like a house price.

   C. Incorrect. Clustering is an unsupervised learning technique used to group similar data points together when there are no predefined labels. This problem uses a dataset with known prices (labels).

2. Question 2Fundamentals of AI and ML [AWS Managed AI/ML Services]

   A developer wants to add a feature to their application that analyzes the sentiment (positive, negative, or neutral) of user comments. They need a managed AWS service that can provide this insight without requiring them to build or train a model. Which service is the best fit?

   • A.Amazon SageMaker
   • B.Amazon Comprehend
   • C.Amazon Translate
   • D.Amazon Rekognition
   Show answer and explanation

   Correct answer: B

   Correct. Amazon Comprehend is a managed natural language processing (NLP) service that offers pre-trained models for tasks like sentiment analysis, entity recognition, and keyphrase extraction via a simple API call.

   Why the other options are wrong

   A. Incorrect. Amazon SageMaker is for building custom models, which requires ML expertise and is not what the developer wants.

   C. Incorrect. Amazon Translate is for translating text between languages, not for analyzing its sentiment.

   D. Incorrect. Amazon Rekognition is for image and video analysis.

3. Question 3Fundamentals of AI and ML [Core Terminology]

   A data scientist uses the K-Means algorithm on customer data. The output, which defines the specific cluster centers and can be used to assign new customers to a group, is called the:

   • A.Dataset
   • B.Model
   • C.Hyperparameters
   • D.Algorithm
   Show answer and explanation

   Correct answer: B

   Correct. The artifact produced after running the K-Means algorithm on the data is the trained K-Means model. This model contains the learned cluster centroids and can be used for inference on new data points.

   Why the other options are wrong

   A. Incorrect. The dataset is the input to the algorithm.

   C. Incorrect. A hyperparameter for K-Means would be 'K', the number of clusters to find, which is an input to the algorithm.

   D. Incorrect. The K-Means algorithm is the procedure used for the training process, not the output itself.

4. Question 4Fundamentals of AI and ML [AI, ML, and Deep Learning]

   What is the primary function of a neural network in the context of deep learning?

   • A.To approximate complex input-output functions by learning patterns through adjusting weights across many layers
   • B.To provide a deterministic, rule-based execution engine that maps specific input parameters directly to predefined outputs
   • C.To schedule and orchestrate the execution of individual data processing and model training steps in a multi-stage ML pipeline
   • D.To store and organize raw training data in a highly structured, relational database format optimized for rapid query retrieval
   Show answer and explanation

   Correct answer: A

   Correct. A neural network is fundamentally a universal function approximator: it learns a mathematical mapping from input features to output predictions by adjusting millions of internal weights during training. Unlike rule-based systems (where the rules are explicitly programmed), the neural network discovers the rules itself from the patterns in data — including non-linear relationships that no human could manually specify.

   Why the other options are wrong

   B. Incorrect. Neural networks learn from data and are probabilistic, which is the opposite of a hard-coded, rule-based engine.

   C. Incorrect. This is the function of an orchestration tool like AWS Step Functions or Amazon SageMaker Pipelines.

   D. Incorrect. This is the function of a relational database.

5. Question 5Fundamentals of AI and ML [Matching ML Techniques to Use Cases]Choose all that apply

   Which of the following business questions are best answered using classification? (Select TWO)

   • A.Will this customer click on the ad (yes/no)?
   • B.How much revenue will we generate next quarter?
   • C.What are the main topics discussed in our customer reviews?
   • D.Which of our three new website designs will this user prefer?
   • E.Which customers are most similar to our highest-spending customer?
   Show answer and explanation

   Correct answer: A, D

   Correct. This is a binary classification problem, where the goal is to predict one of two discrete categories.

   Correct. This is a multi-class classification problem, where the goal is to predict which of the three discrete categories (designs) the user belongs to in terms of preference.

   Why the other options are wrong

   B. Incorrect. This requires predicting a continuous numerical value, which is a regression problem.

   C. Incorrect. Discovering topics without predefined categories is an unsupervised learning task (clustering or topic modeling).

   E. Incorrect. This is a similarity or clustering problem.