AWS Certified AI Practitioner (AIF-C01): Applications of Foundation Models
Field | Description / Template |
|---|---|
Purpose | This course helps learners understand how to design, build, and evaluate applications powered by foundation models. It covers key concepts such as model selection, prompt engineering, retrieval-augmented generation (RAG), fine-tuning, and performance evaluation. Learners will also explore cost-performance tradeoffs and practical design considerations for deploying AI applications on AWS, with alignment to the AWS Certified AI Practitioner (AIF-C01) exam. |
Audience | Beginners, developers, product managers, business professionals, and AWS certification aspirants interested in building applications using Generative AI and foundation models. |
Role | AI Practitioner, Prompt Engineer, Developer, ML Engineer (Beginner), Product Manager, Technical Consultant. |
Domain | Generative AI, AI/ML, Cloud Computing |
Skill Level | Beginner |
Style | Conceptual learning with practical design scenarios, real-world use cases, AWS service context, and exam-focused preparation with tips and review questions. |
Duration | 6–10 hours |
Related Technologies | AWS Bedrock, Amazon SageMaker, Foundation Models (LLMs), Vector Databases, Retrieval-Augmented Generation (RAG), Prompt Engineering |
Course Description
This course provides a practical understanding of how to build and deploy applications using foundation models within the AWS ecosystem. Learners will explore essential design considerations such as selecting the right model, configuring inference parameters, and implementing retrieval-augmented generation (RAG) for improved accuracy.
The course also dives into prompt engineering techniques, highlighting best practices, benefits, and limitations. Learners will gain insights into training and fine-tuning foundation models, including data preparation and customization strategies.
Additionally, the course covers evaluation methods for foundation models, focusing on performance metrics and aligning outputs with business objectives. With exam-focused reviews and real-world context, this course prepares learners for the AWS Certified AI Practitioner (AIF-C01) certification.
Who is this course for
Beginners exploring Generative AI applications
Developers building AI-powered applications
Product managers working on AI-driven products
AWS certification aspirants (AI Practitioner)
Professionals interested in prompt engineering and LLM applications
Course Objectives
By the end of this course, learners will be able to:
Select appropriate foundation models for specific use cases
Configure inference parameters and optimize model outputs
Implement retrieval-augmented generation (RAG) architectures
Apply effective prompt engineering techniques and best practices
Understand methods for training and fine-tuning foundation models
Prepare and manage data for model customization
Evaluate model performance using technical and business metrics
Understand cost-performance tradeoffs in AI applications
Prepare effectively for the AWS Certified AI Practitioner (AIF-C01) exam
Prerequisites
Basic understanding of AI/ML or Generative AI concepts
Familiarity with cloud computing fundamentals
No hands-on experience with foundation models required
Interest in building AI-powered applications
Course outline
Section 1: Design Considerations for Foundation Model Applications
Selecting Foundation Models
Inference Parameters
Retrieval-augmented Generation (RAG)
Vector Storage Solutions on AWS
Cost Tradeoffs for Customization
Agents for Multi-step Tasks
Exam Tips
Section 2: Prompt Engineering Techniques
Fundamentals of Prompt Engineering
Prompt Engineering Techniques
Benefits and Best Practices
Risks and Limitations of Prompt Engineering
Exam Tips
Section 3: Training and Fine-tuning Foundation Models
Key Elements of Training Foundation Models
Methods for Fine-tuning Foundation Models
Preparing Data to Fine-tune a Foundation Model
Exam Tips
Section 4: Evaluating Foundation Model Performance
Evaluation Approaches for Foundation Models
Performance Metrics
Business Objective Alignment
Exam Tips
Section 5: Exam Question Review
Design Considerations for Foundation Models
Prompt Engineering Techniques
Training and Fine-tuning Foundation Models
Evaluating Foundation Model Performance