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Keep shoppingAWS Certified AI Practitioner (AIF-C01) - 3 Practice Test
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AWS Certified AI Practitioner (AIF-C01) - 3 Practice Test
AWS Certified AI Practitioner (AIF-C01) -3 Practice Test + Bonus Use case Based Questions
Created byRavi Singh
Last updated 4/2025
English
What you'll learn
- Gain an understanding of AI, ML, and generative AI concepts, methods, and strategies, both in general and specifically on AWS.
- Learn how to appropriately use AI/ML and generative AI technologies to ask relevant questions within your organization.
- Identify the right types of AI/ML technologies to apply to specific use cases.
- Apply AI, ML, and generative AI technologies responsibly.
- Learn the foundational concepts of artificial intelligence (AI) and machine learning (ML), including key terms, algorithms, and how AI/ML solutions are applied
- Understand the differences between supervised learning, unsupervised learning, and reinforcement learning.
- Gain the ability to identify and use core AWS services such as Amazon SageMaker, AWS Deep Learning AMIs, AWS Lambda, Amazon Rekognition, Amazon Comprehend, and
- Understand how to apply these services for tasks like natural language processing (NLP), computer vision, and predictive analytics.
- Learn the stages of the machine learning lifecycle, including data collection, data preprocessing, feature engineering, model training, model evaluation, deploy
- Understand how to implement these stages using AWS services, such as Amazon SageMaker, for building and deploying ML models.
- Gain skills in preparing and processing data for ML projects using AWS tools like Amazon SageMaker Data Wrangler for data cleaning, transforming, and feature en
- Learn how to leverage AWS Glue for data integration and preparation in AI/ML pipelines.
- Understand how to identify business problems that can be addressed using AI/ML solutions on AWS, such as improving customer experiences, automating business pro
- Learn how to translate business requirements into AI/ML models and solutions using AWS tools and services.
- Learn the basic principles of securing AI/ML models and data, including encryption, access control, and compliance considerations when working with AI/ML soluti
- Understand AWS security services, such as AWS Identity and Access Management (IAM) and Amazon Macie, and how they can be used to protect sensitive data in AI/ML
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Included in This Course
161 questions
Description
AWS Certified AI Practitioner (AIF-C01) Exam Guide
Introduction
The AWS Certified AI Practitioner (AIF-C01) exam is intended for individuals who can effectively demonstrate overall knowledge of AI/ML, generative AI technologies, and associated AWS services and tools, independent of a specific job role. The exam also validates a candidate’s ability to complete the following tasks: • Understand AI, ML, and generative AI concepts, methods, and strategies in general and on AWS. • Understand the appropriate use of AI/ML and generative AI technologies to ask relevant questions within the candidate’s organization. • Determine the correct types of AI/ML technologies to apply to specific use cases. • Use AI, ML, and generative AI technologies responsibly.
Target candidate description
The target candidate should have up to 6 months of exposure to AI/ML technologies on AWS. The target candidate uses but does not necessarily build AI/ML solutions on AWS.
Recommended AWS knowledge
The target candidate should have the following AWS knowledge: • Familiarity with the core AWS services (for example, Amazon EC2, Amazon S3, AWS Lambda, and Amazon SageMaker) and AWS core services use cases • Familiarity with the AWS shared responsibility model for security and compliance in the AWS Cloud • Familiarity with AWS Identity and Access Management (IAM) for securing and controlling access to AWS resources • Familiarity with the AWS global infrastructure, including the concepts of AWS Regions, Availability Zones, and edge locations • Familiarity with AWS service pricing models
Exam content
Question types
The exam contains one or more of the following question types: •
Multiple choice:
Has one correct response and three incorrect responses (distractors).
• Multiple response:
Has two or more correct responses out of five or more response options. You must select all the correct responses to receive credit for the question. • Ordering:
Has a list of 3–5 responses to complete a specified task. You must select the correct responses and place the responses in the correct order to receive credit for the question. • Matching:
Has a list of responses to match with a list of 3–7 prompts. You must match all the pairs correctly to receive credit for the question.
• Case study: Has one scenario with two or more questions about the scenario. The scenario is the same for each question in the case study. Each question in the case study will be evaluated separately. You will receive credit for each question that you answer correctly in the case study.
Who this course is for:
- Gain an understanding of AI, ML, and generative AI concepts, methods, and strategies, both in general and specifically on AWS.
- Learn how to appropriately use AI/ML and generative AI technologies to ask relevant questions within your organization.
- Identify the right types of AI/ML technologies to apply to specific use cases.
- Apply AI, ML, and generative AI technologies responsibly.
- Individuals looking to start a career in AI and ML who want to demonstrate their basic understanding of AI concepts, tools, and AWS services.
- Learners with little to no formal experience in AI/ML but interested in exploring the foundational aspects of AI and machine learning on AWS.
- Individuals who work in roles that require an understanding of AI/ML technologies but do not need deep technical expertise.
- Business analysts, product managers, and decision-makers who wish to use AI to drive business decisions and improve operational efficiency, and who need to understand how AI fits into the AWS ecosystem.
- Professionals who are familiar with the basic concepts of AWS and want to expand their knowledge to include AI/ML services offered by AWS.
- Learners already holding the AWS Certified Cloud Practitioner certification or with similar experience, looking to dive deeper into AI services provided by AWS.
- IT professionals such as software engineers, data engineers, and system administrators who are looking to transition into AI/ML roles and want a structured path to gain fundamental skills.
- Individuals who already have experience with cloud computing and are interested in applying AI/ML in their work to enhance data-driven applications.
- Learners interested in working with AWS AI services like Amazon SageMaker, AWS Deep Learning AMIs, and others for AI-related tasks, but who do not need an in-depth understanding of complex machine learning algorithms and models.
- This includes learners who want to understand how AWS AI tools can be used for real-world applications such as natural language processing, computer vision, and more.