AWS Certified AI Practitioner (AIF-C01)
Field | Description |
|---|---|
Purpose | This course prepares learners for the AWS Certified AI Practitioner (AIF-C01) exam while building a strong foundation in Artificial Intelligence (AI), Machine Learning (ML), and Generative AI. It covers core concepts, real-world applications, AWS AI/ML services, and responsible AI practices. Learners will understand how to design, evaluate, and secure AI solutions using AWS, along with practical insights into foundation models and prompt engineering. |
Audience | Beginners, business analysts, non-technical professionals, students, and early-career technologists interested in AI/ML concepts and AWS AI services. |
Role | AI Practitioner, Cloud Practitioner, Business Analyst, Product Manager, Technical Consultant, Pre-sales Engineer. |
Domain | AI/ML, Generative AI, Cloud Computing |
Skill Level | Beginner |
Style | Conceptual learning with practical examples, AWS service walkthroughs, exam-focused preparation, and real-world use cases. Includes demos and review questions. |
Duration | 5 Days |
Related Technologies | Amazon SageMaker, AWS Bedrock, AWS AI Services (Rekognition, Comprehend, Lex, Polly, Textract), Foundation Models, Prompt Engineering |
Course Description
The AWS Certified AI Practitioner course is designed to introduce learners to the fundamentals of Artificial Intelligence, Machine Learning, and Generative AI within the AWS ecosystem. It provides a comprehensive overview of the ML pipeline, AWS-managed AI services, and modern AI applications, including foundation models and prompt engineering.
The course also emphasizes responsible AI practices, governance, security, and compliance considerations when building AI solutions. With a strong focus on exam readiness, it includes practice questions and structured reviews aligned with the AIF-C01 certification.
Who is this course for
Individuals new to AI/ML and cloud technologies
Business and non-technical professionals working with AI-driven products
Students exploring careers in AI or cloud computing
Professionals preparing for AWS AI Practitioner certification
Anyone interested in understanding Generative AI and foundation models
Course Objectives
By the end of this course, learners will be able to:
Understand fundamental AI and ML concepts and workflows
Describe the machine learning pipeline and AWS AI services
Explain Generative AI concepts and real-world use cases
Work with foundation models and apply prompt engineering techniques
Identify responsible AI practices and ethical considerations
Understand AI security, governance, and compliance on AWS
Prepare effectively for the AWS Certified AI Practitioner (AIF-C01) exam
Prerequisites
Basic understanding of cloud computing concepts (helpful but not required)
General awareness of technology or IT concepts
No prior experience in AI/ML required
Familiarity with AWS basics is a plus but not mandatory
Course outline
Section 1: Everything You Need to Know about the AWS Certified AI Practitioner Exam
Section 2: Fundamentals of AI and ML (Learn More)
Introducing Basic AI and ML Concepts
The Machine Learning Pipeline
AWS Managed AI/ML Services and Applications
Unpacking Amazon SageMaker
Exam Question Review
Section 3: Fundamentals of Generative AI (Learn More)
Generative AI Concepts
Use Cases for Generative AI
Generative AI in AWS
Exam Question Review
Section 4: Guidelines for Responsible AI (Learn More)
Responsible AI Systems
Building Responsible AI with AWS Tools
Exam Question Review
Section 5: Applications of Foundation Models (Learn More)
Design Considerations for Foundation Model Applications
Prompt Engineering Techniques
Training and Fine-tuning Foundation Models
Evaluating Foundation Model Performance
Exam Questions Review
Section 6: Security, Compliance, and Governance for AI Solutions (Learn More)
Securing AI Systems
Governance and Compliance for AI Systems
Exam Questions Review