Course Overview

This fundamental-level exam preparation course is designed to help you get ready for the AWS Certified AI Practitioner (AIF-C01) exam. The course breaks down each domain of the exam—covering AI/ML fundamentals, AWS AI services, use cases, and responsible AI—while aligning them with hands-on labs and real-world scenarios. You’ll evaluate your understanding through guided walkthroughs of exam-style questions, learn to recognize distractors, and identify areas that need further study. With interactive knowledge checks and a final pretest, you’ll build the confidence to take the exam and validate your AI competency in the AWS Cloud.

After completing this course of training, you will be able to:

  • Understand foundational AI and ML concepts and how they apply within the AWS ecosystem.
  • Identify and describe key AWS AI/ML services and their appropriate use cases.
  • Recognize real-world business problems that can be solved using AI/ML solutions on AWS.
  • Apply responsible AI principles and understand ethical considerations in AI use.
  • Develop test-taking strategies to effectively tackle exam-style questions and avoid common distractors.
  • Evaluate your readiness for the AIF-C01 exam through interactive knowledge checks and a final pretest.
  • Gain practical experience with AWS AI and ML services through guided, hands-on labs.
  • Build the confidence and skills needed to successfully attempt and pass the AWS Certified AI Practitioner exam.

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Key Features:

  • Complete Exam Coverage: Covers all AWS Certified AI Practitioner AIF-C01 exam domains including AI/ML fundamentals, AWS services, use cases, and responsible AI.

  • Beginner-Friendly: Designed for non-technical learners to build foundational AI and ML knowledge.

  • Structured Learning Path: Provides a clear, step-by-step approach aligned with exam objectives.

  • Exam-Style Question Walkthroughs: Includes guided practice with questions and tips to identify distractors.

  • Interactive Knowledge Checks: Reinforces learning with quizzes and checkpoints throughout the course.

  • Responsible AI Focus: Highlights ethical AI practices and responsible AI implementation on AWS.

Who should Attend?

  • Business analysts
  • IT support professionals
  • Marketing specialists
  • Product or project managers
  • Line-of-business or IT managers
  • Sales professionals

Prerequisites:

Up to 6 months of exposure to AI/ML technologies on AWS

Why choose CloudThat as your AWS certification training partner?

  • Expert Instructors: CloudThat's courses are led by industry experts with extensive experience in AI and AWS, ensuring high-quality instruction.
  • Hands-On Learning: Emphasis on practical, hands-on labs and real-world demos to provide participants with valuable, applicable skills.
  • Comprehensive Curriculum: Courses cover a wide range of topics, from introductory concepts to advanced implementation, offering a well-rounded learning experience.
  • Focus on Responsible AI: Training includes responsible AI principles, ensuring ethical practices and compliance with industry standards.
  • Career Advancement: CloudThat's training programs are designed to enhance career prospects, preparing participants for various roles in AI and machine learning.
  • Post-Training Support: CloudThat offers post-training support, additional resources, and forums for ongoing learning and development

Course Outline Download Course Outline

  • Task Statement 1.1: Explain basic AI concepts and terminologies
  • Task Statement 1.2: Identify practical use cases for AI
  • Task Statement 1.3: Describe the ML development lifecycle
  • Walkthrough Questions

  • Task Statement 2.1: Explain the basic concepts of generative AI
  • Task Statement 2.2: Understand the capabilities and limitations of generative AI for solving business problems
  • Task Statement 2.3: Describe AWS infrastructure and technologies for building generative AI applications
  • Walkthrough Questions

  • Task Statement 3.1: Describe design considerations for applications that use foundation models
  • Task Statement 3.2: Choose effective prompt engineering techniques
  • Task Statement 3.3: Describe the training and fine-tuning process for foundation models
  • Task Statement 3.4: Describe methods to evaluate foundation model performance
  • Walkthrough Questions

  • Task Statement 4.1: Explain the development of AI systems that are responsible
  • Task Statement 4.2: Recognize the importance of transparent and explainable models
  • Walkthrough Questions

  • Task Statement 5.1: Explain methods to secure AI systems
  • Task Statement 5.2: Recognize governance and compliance regulations for AI systems
  • Walkthrough Questions

Certification Details:

    AWS Certified AI Practitioner

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Course ID: 25302

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FAQs:

This training can open doors to AI-related roles such as AI Analyst, Cloud Support Associate (AI/ML), Business Analyst (AI focus), Junior ML Engineer, and entry-level roles in AI product teams.

Entry-level AI practitioners can expect salaries ranging from ₹5 to ₹10 lakhs per annum in India and $65,000 to $85,000 per year in the US, depending on the industry and role.

You'll learn foundational AI/ML concepts, AWS AI services like Amazon Rekognition, Lex, Comprehend, Bedrock, and responsible AI principles—all within a cloud context.

It provides recognized validation of your AI fluency on AWS, helping you transition into AI-aligned roles or move toward more advanced certifications and responsibilities.

Yes. The course is designed to help you successfully pass the AWS Certified AI Practitioner (AIF-C01) exam and validate your foundational knowledge in AI/ML on AWS.

No technical background is required, but familiarity with basic cloud concepts or AWS Cloud Practitioner-level knowledge is helpful.

You’ll get access to discussion forums, knowledge-check quizzes, a pretest, and optional mentorship or study group support to reinforce your learning and exam preparation.

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