Idigisys

AWS

AWS Certified AI Practitioner

The AWS Certified AI Practitioner (AIF-C01) exam is intended for individuals who can effectively demonstrate overall knowledge…

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 

 

 

 

 

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What Will You Learn?

  • Understand basic AI/ML concepts, terminologies, and methods.
  • Differentiate between AI, ML, and deep learning.
  • Recognize different types of inferencing (batch, real-time).
  • Identify various types of data used in AI models.
  • Learn about supervised, unsupervised, and reinforcement learning.
  • Explore AI/ML use cases and when AI solutions are appropriate.
  • Understand the ML development lifecycle and MLOps concepts.

Course Curriculum

Fundamentals of AI and ML

  • Explain basic AI concepts and terminologies
  • Identify practical use cases for AI.
  • Describe the ML development lifecycle.
  • PPT

Fundamentals of Generative AI

Applications of Foundation Models

Guidelines for Responsible AI

Security, Compliance, and Governance for AI Solutions

Student Ratings & Reviews

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The cloud training program at Idigisys transformed my career. The hands-on approach and expert mentorship helped me secure a cloud engineer role at HCL Technologies. Highly recommended!
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