Course Objectives
This course is designed to equip you with the essential knowledge of AI, machine learning, and generative AI security—all tailored to help you succeed in the certification exam. The main objectives include:- Teaching the fundamentals of AI and machine learning.
- Introducing the basics of generative AI, which differs from traditional AI and machine learning.
- Demonstrating how to integrate foundation models within AI applications, especially those provided by AWS, to enhance your non-AI systems.
- Highlighting guidelines for responsible and ethical AI practices, a critical aspect of the exam.
- Offering an overview of security, compliance, and governance for AI solutions, including key issues such as hallucinations, plagiarism, and data poisoning.

Intended Audience
This course targets individuals with a basic understanding of essential AWS concepts, which include:- AWS Shared Responsibility Model
- AWS Identity and Access Management (IAM)
- AWS Global Infrastructure
- AWS Pricing Models

Course Structure
The curriculum is divided into five key content domains across seven sections, which include:- Fundamentals of AI and Machine Learning
- Fundamentals of Generative AI
- Applications of Foundation Models
- Guidelines for Ethical and Responsible AI Use
- Security, Compliance, and Governance of AI Solutions

Introduction and Closing
The introductory segment clearly communicates the course purpose, key content areas, target audience, and effective strategies for preparation. It answers crucial questions such as:- Why should you take this course?
- What topics will be covered?
- Who is the course designed for?
- How should you prepare for the material?

Exam Preparation
Similar to our other AWS courses, exam preparation is a crucial component here. Both pre-assessment and post-assessment exams mimic the real certification test format—65 questions to be answered within roughly 100 minutes. From my own experience taking the exam, I can affirm that practicing under simulated exam conditions significantly enhances performance. All content sections—covering fundamentals of AI, generative AI, foundation models, ethical AI use, and security—are directly applicable to what you’ll face in the AWS AI Practitioner exam.
Study Tips
When approaching this course, consider the following study tips to maximize your learning:- Be Patient: Learning new concepts can be challenging initially, but persistence pays off.
- Stay Consistent: Dedicate at least 15-30 minutes to study each day.
- Engage Actively: Participate in hands-on practice by exploring AWS services, engaging with labs, and watching tutorials or reading documentation about AWS Bedrock or SageMaker.
- Eliminate Distractions: Keep a focused study environment to utilize your time effectively.

If you take the exam before February 2025, you will earn not only the AWS certification badge but also an early adopter badge. This is an excellent incentive to begin your preparation without delay.
Course Summary
This course is best suited for individuals who already have cloud practitioner-level knowledge or equivalent AWS experience. It includes:- Five content modules that align with the AWS AI Practitioner exam guide.
- Pre- and post-assessments, quizzes, demonstrations, and interactive games to reinforce learning.
- A primary focus on theoretical concepts to deliver a robust understanding in preparation for the exam.
