<?xml version="1.0" encoding="utf-8" ?>
<!DOCTYPE FL_Course SYSTEM "https://www.flane.de/dtd/fl_course095.dtd"><?xml-stylesheet type="text/xsl" href="https://portal.flane.ch/css/xml-course.xsl"?><course productid="36122" language="fr" source="https://portal.flane.ch/swisscom/fr/xml-course/amazon-epcaip" lastchanged="2025-09-12T13:02:32+02:00" parent="https://portal.flane.ch/swisscom/fr/xml-courses"><title>Exam Prep: AWS Certified AI Practitioner (AIF-C01)</title><productcode>EPCAIP</productcode><vendorcode>AW</vendorcode><vendorname>Amazon Web Services</vendorname><fullproductcode>AW-EPCAIP</fullproductcode><version>1.0</version><objective>&lt;p&gt;In this course, you will learn to:
&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Identify the scope and content tested by the AWS Certified AI Practitioner (AIF-C01) exam.&lt;/li&gt;&lt;li&gt;Practice exam style questions and evaluate your preparation strategy.&lt;/li&gt;&lt;li&gt;Examine use cases and differentiate between them.&lt;/li&gt;&lt;/ul&gt;</objective><essentials>&lt;p&gt;You are not required to take any specific training before taking this course. However, the following prerequisite knowledge is recommended prior to taking the AWS Certified AI Practitioner (AIF-C01) exam.&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Recommended AWS knowledge&lt;/strong&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Familiarity with the core AWS services (for example, Amazon EC2, Amazon S3, AWS Lambda,and Amazon SageMaker AI) and AWS core services use cases.&lt;/li&gt;&lt;li&gt;Suggested to have up to 6 months of exposure to AI and ML technologies on AWS.&lt;/li&gt;&lt;li&gt;Are familiar with, but do not necessarily build, solutions using AI and ML technologies on AWS.&lt;/li&gt;&lt;li&gt;Familiarity with the AWS shared responsibility model for security and compliance in the AWS Cloud.&lt;/li&gt;&lt;li&gt;Familiarity with AWS Identity and Access Management (IAM) for securing and controlling access to AWS resources.&lt;/li&gt;&lt;li&gt;Familiarity with the AWS global infrastructure, including the concepts of AWS Regions, Availability Zones, and edge locations.&lt;/li&gt;&lt;li&gt;Familiarity with AWS service pricing models.&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;strong&gt;Recommended courses&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;The following courses (or similar) are recommended but not required.&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Fundamentals of Machine Learning and Artificial Intelligence (1 hour)&lt;/li&gt;&lt;li&gt;Exploring Artificial Intelligence Use Cases and Applications (1 hour)&lt;/li&gt;&lt;li&gt;Responsible Artificial Intelligence Practices (1 hour)&lt;/li&gt;&lt;li&gt;Developing Machine Learning Solutions (1 hour)&lt;/li&gt;&lt;li&gt;Developing Generative Artificial Intelligence Solutions (1 hour)&lt;/li&gt;&lt;li&gt;Essentials of Prompt Engineering (1 hour)&lt;/li&gt;&lt;li&gt;Optimizing Foundation Models (1 hour)&lt;/li&gt;&lt;li&gt;Security, Compliance, and Governance for AI Solutions (1 hour)&lt;/li&gt;&lt;li&gt;&lt;span class=&quot;cms-link-marked&quot;&gt;&lt;a class=&quot;fl-href-prod&quot; href=&quot;/swisscom/fr/course/amazon-genaiex&quot;&gt;&lt;svg role=&quot;img&quot; aria-hidden=&quot;true&quot; focusable=&quot;false&quot; data-nosnippet class=&quot;cms-linkmark&quot;&gt;&lt;use xlink:href=&quot;/css/img/icnset-linkmarks.svg#linkmark&quot;&gt;&lt;/use&gt;&lt;/svg&gt;Generative AI for Executives &lt;span class=&quot;fl-prod-pcode&quot;&gt;(GENAIEX)&lt;/span&gt;&lt;/a&gt;&lt;/span&gt;&lt;/li&gt;&lt;li&gt;Amazon Q Business Getting Started (0.75 hour)&lt;/li&gt;&lt;li&gt;Amazon Bedrock Getting Started (1 hour)&lt;/li&gt;&lt;li&gt;Getting Started with Amazon Comprehend: Custom Classification (1.25 hours)&lt;/li&gt;&lt;li&gt;Build a Question-Answering Bot Using Generative AI (1.5 hours)&lt;/li&gt;&lt;/ul&gt;</essentials><audience>&lt;ul&gt;
&lt;li&gt;This course is intended for individuals who are preparing for the AWS Certified AI Practitioner (AIF-C01) exam.&lt;/li&gt;&lt;/ul&gt;</audience><contents>&lt;p&gt;This course includes subject overview presentations, exam-style questions, use cases, and group discussions and activities.&lt;/p&gt;</contents><outline>&lt;p&gt;&lt;strong&gt;Introduction&lt;/strong&gt;&lt;/p&gt;
&lt;p&gt;&lt;strong&gt;Domain 1: Fundamentals of AI and ML&lt;/strong&gt;
&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;1.1: Explain basic AI concepts and terminologies&lt;/li&gt;&lt;li&gt;1.2: Identify practical use cases for AI&lt;/li&gt;&lt;li&gt;1.3: Describe the ML development lifecycle&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;
&lt;strong&gt;Domain 2: Fundamentals of Generative AI&lt;/strong&gt;
&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;2.1: Explain the basic concepts of generative AI&lt;/li&gt;&lt;li&gt;2.2: Understand the capabilities and limitations of generative AI for solving business problems&lt;/li&gt;&lt;li&gt;2.3: Describe AWS infrastructure and technologies for building generative AI applications&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;strong&gt;Domain 3: Applications of Foundation Models&lt;/strong&gt;
&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;3.1: Describe design considerations for applications that use foundation models&lt;/li&gt;&lt;li&gt;3.2: Choose effective prompt engineering techniques&lt;/li&gt;&lt;li&gt;3.3: Describe the training and fine-tuning process for foundation models&lt;/li&gt;&lt;li&gt;3.4: Describe methods to evaluate foundation model performance&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;strong&gt;Domain 4: Guidelines for Responsible AI&lt;/strong&gt;
&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;4.1: Explain the development of AI systems that are responsible&lt;/li&gt;&lt;li&gt;4.2: Recognize the importance of transparent and explainable models&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;
&lt;strong&gt;Domain 5: Security, Compliance, and Governance for AI Solutions&lt;/strong&gt;
&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;5.1: Explain methods to secure AI systems&lt;/li&gt;&lt;li&gt;5.2: Recognize governance and compliance regulations for AI systems&lt;/li&gt;&lt;/ul&gt;&lt;p&gt;&lt;strong&gt;Course completion&lt;/strong&gt;&lt;/p&gt;</outline><objective_plain>In this course, you will learn to:



- Identify the scope and content tested by the AWS Certified AI Practitioner (AIF-C01) exam.
- Practice exam style questions and evaluate your preparation strategy.
- Examine use cases and differentiate between them.</objective_plain><essentials_plain>You are not required to take any specific training before taking this course. However, the following prerequisite knowledge is recommended prior to taking the AWS Certified AI Practitioner (AIF-C01) exam.

Recommended AWS knowledge


- Familiarity with the core AWS services (for example, Amazon EC2, Amazon S3, AWS Lambda,and Amazon SageMaker AI) and AWS core services use cases.
- Suggested to have up to 6 months of exposure to AI and ML technologies on AWS.
- Are familiar with, but do not necessarily build, solutions using AI and ML technologies on AWS.
- 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.
Recommended courses

The following courses (or similar) are recommended but not required.


- Fundamentals of Machine Learning and Artificial Intelligence (1 hour)
- Exploring Artificial Intelligence Use Cases and Applications (1 hour)
- Responsible Artificial Intelligence Practices (1 hour)
- Developing Machine Learning Solutions (1 hour)
- Developing Generative Artificial Intelligence Solutions (1 hour)
- Essentials of Prompt Engineering (1 hour)
- Optimizing Foundation Models (1 hour)
- Security, Compliance, and Governance for AI Solutions (1 hour)
- Generative AI for Executives (GENAIEX)
- Amazon Q Business Getting Started (0.75 hour)
- Amazon Bedrock Getting Started (1 hour)
- Getting Started with Amazon Comprehend: Custom Classification (1.25 hours)
- Build a Question-Answering Bot Using Generative AI (1.5 hours)</essentials_plain><audience_plain>- This course is intended for individuals who are preparing for the AWS Certified AI Practitioner (AIF-C01) exam.</audience_plain><contents_plain>This course includes subject overview presentations, exam-style questions, use cases, and group discussions and activities.</contents_plain><outline_plain>Introduction

Domain 1: Fundamentals of AI and ML



- 1.1: Explain basic AI concepts and terminologies
- 1.2: Identify practical use cases for AI
- 1.3: Describe the ML development lifecycle

Domain 2: Fundamentals of Generative AI



- 2.1: Explain the basic concepts of generative AI
- 2.2: Understand the capabilities and limitations of generative AI for solving business problems
- 2.3: Describe AWS infrastructure and technologies for building generative AI applications
Domain 3: Applications of Foundation Models



- 3.1: Describe design considerations for applications that use foundation models
- 3.2: Choose effective prompt engineering techniques
- 3.3: Describe the training and fine-tuning process for foundation models
- 3.4: Describe methods to evaluate foundation model performance
Domain 4: Guidelines for Responsible AI



- 4.1: Explain the development of AI systems that are responsible
- 4.2: Recognize the importance of transparent and explainable models

Domain 5: Security, Compliance, and Governance for AI Solutions



- 5.1: Explain methods to secure AI systems
- 5.2: Recognize governance and compliance regulations for AI systems
Course completion</outline_plain><duration unit="d" days="1">1 jour</duration><pricelist><price country="US" currency="USD">675.00</price><price country="CA" currency="CAD">930.00</price><price country="GB" currency="GBP">900.00</price><price country="DE" currency="EUR">750.00</price><price country="IT" currency="EUR">450.00</price><price country="AT" currency="EUR">750.00</price><price country="SE" currency="EUR">750.00</price><price country="SI" currency="EUR">750.00</price><price country="NL" currency="EUR">750.00</price><price country="CH" currency="CHF">750.00</price></pricelist><miles/></course>