AWS Certified AI Practitioner Training
This one-day, foundational course validates knowledge of artificial intelligence (AI), machine learning (ML), and generative AI concepts and use cases . It is designed to sharpen your competitive edge and position you for career growth and higher earnings .b The course covers key concepts, methods, and strategies for AI, ML, and generative AI, both in general and on AWS . It also teaches you to identify appropriate technologies for specific use cases and to use these technologies responsibly .
Certified AI Practitioner on AWS
Course Overview
AWS Certified AI Practitioner validates in-demand knowledge of artificial intelligence (AI), machine learning (ML), and generative AI concepts and use cases. Sharpen your competitive edge and position yourself for career growth and higher earnings. 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.
Course Outline
- Module 1: Machine Learning (ML) Fundamentals
- Describe the ML development lifecycle.
- Module 2: Fundamentals of Generative AI
- Explain the basic concepts of generative AI.
- Understand the capabilities and limitations of generative AI for solving business problems.
- Describe AWS infrastructure and technologies for building generative AI applications.
- Module 3: Applications of Foundation Models
- Describe design considerations for applications that use foundation models.
- Choose effective prompt engineering techniques.
- Describe the training and fine-tuning process for foundation models.
- Describe methods to evaluate foundation model performance.
- Module 4: Guidelines for Responsible AI
- Explain the development of AI systems that are responsible.
- Recognize the importance of transparent and explainable models.
- Module 5: Security, Compliance, and Governance for AI Solutions
- Explain methods to secure AI systems.
- Recognize governance and compliance regulations for AI systems.
Prerequisites
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
Follow-On Courses
Related training topics
Justify your training
Use this sample request letter — copy it into an email to your manager and personalize the bracketed details to make the case for the time and budget.
Sample training request letter
Subject: Request for AI & AI Security training from Applied Technology Academy
[Decision Maker Name],
I'm writing to request time and budget approval to complete Applied Technology Academy's course, AWS Certified AI Practitioner Training. The information below outlines how this training benefits our organization, the tasks I'll be able to perform after completing it, and relevant cost and funding details.
Course Description
This one-day, foundational course validates knowledge of artificial intelligence (AI), machine learning (ML), and generative AI concepts and use cases . It is designed to sharpen your competitive edge and position you for career growth and higher earnings .b The course covers key concepts, methods, and strategies for AI, ML, and generative AI, both in general and on AWS . It also teaches you to identify appropriate technologies for specific use cases and to use these technologies responsibly . Applied Technology Academy is an award-winning, SBA-certified woman-owned training provider (est. 2008) whose instructors are active practitioners; the course is hands-on with virtual labs and a learn-by-doing methodology.
Course Objectives
Once I've completed the course, I'll have hands-on, job-ready skills in ai & ai security that I can apply immediately to our work.
Expected Organizational Benefits
After completing this course, I will be better equipped to apply these skills directly to our projects, reduce our reliance on outside expertise, strengthen our team's capabilities, and share what I learn with colleagues.
Expected Cost & Funding
Course fee: [request an itemized quote at the link below]. Applied Technology Academy supports multiple funding paths that may reduce or cover this cost: GSA MAS purchasing and government purchase orders, military credentialing funding (Army CA, AF COOL, CG COOL), VA GI Bill and VR&E, ATA Flexible Spending, and student financing. Private team cohorts are available if colleagues should attend with me.
Conclusion
This training provides practical, hands-on experience I can apply immediately to strengthen our work in ai & ai security. Additional course information is available at https://appliedtechnologyacademy.com/aws-training/aws-certified-ai-practitioner-on-aws/.
Thank you for your consideration,
[Your Name]
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