Fundamentals of AWS AI and ML Solutions

Fundamentals of AWS AI and ML Solutions course is designed for cloud engineers, developers, and technical professionals who want to build a strong foundation in artificial intelligence (AI), machine learning (ML), and deep learning using AWS services. The course focuses on helping learners understand how machine learning systems work, how to identify the right ML approach for real-world problems, and how to use managed AWS AI/ML services to accelerate solution development. Learners will progress from core AI and ML fundamentals to hands-on exposure with Amazon SageMaker and a wide range of AWS AI services used for language, vision, speech, and intelligent automation use cases. The course comprises approximately 4–5 hours of video content, organised into three comprehensive modules, each divided into focused technical lessons. To reinforce learning, each module includes quizzes and in-video knowledge checks, allowing learners to validate both conceptual understanding and practical knowledge as they progress. - Module 1: Fundamentals of AI & ML - Module 2: Amazon Sagemaker - Module 3: AWS Managed AI Services By the end of the course, learners will be confident in understanding ML workflows, evaluating models, and choosing the right AWS AI services for business and technical requirements. - Understand how ML and deep learning models are operationalized in production systems. - Learn to prepare, manage, and operationalize ML data and features using SageMaker Data Wrangler, Feature Store, and Model Monitor. - Apply human-in-the-loop workflows to improve accuracy and reliability

• Understand the complete machine learning lifecycle from data preparation to evaluation
• Prepare and manage ML data and features using SageMaker tools
• Identify appropriate AWS AI services for business and application needs

• Basic computer and internet skills
• Ability to follow English instructions and complete practical exercises