AWS Fundamentals of Machine Learning and Artificial Intelligence

Investigate the foundations of AI and machine learning

Artificial intelligence is behind a growing range of tools, services, and digital experiences.

On this introductory course, you’ll explore the core concepts that underpin artificial intelligence (AI), machine learning (ML), deep learning, and generative AI, while seeing how these technologies are used in practice with AWS.

You’ll begin by distinguishing between different branches of AI and examining how models learn from data.

Along the way, you’ll become familiar with common terminology, algorithms, and data types that shape modern AI and machine learning systems.

Recognise where AI and ML add value

Explore real-world applications across areas such as natural language processing, computer vision, automation, and business decision-making.

You’ll consider how different AI and ML approaches suit different problems and why selecting the right method matters.

Connect AI concepts to AWS services

Discover how AWS supports AI and machine learning through services designed for model development, generative AI, and intelligent applications.

You’ll start to see how tools such as Amazon SageMaker and Amazon Bedrock fit into the wider AWS AI ecosystem.

Lay the groundwork for more advanced AI practice

Build the vocabulary and conceptual understanding needed to progress into model development, generative AI solutions, prompt engineering, security, governance, and responsible AI.

By the end, you’ll be able to explain the core differences between AI, ML, deep learning, and generative AI and recognise how AWS services can support a range of practical use cases.

This course is for developers, analysts, business and technology professionals, data professionals, and aspiring AI practitioners who want a clear introduction to AI and machine learning with AWS. Advanced AI or ML experience is not required.

This course is for developers, analysts, business and technology professionals, data professionals, and aspiring AI practitioners who want a clear introduction to AI and machine learning with AWS. Advanced AI or ML experience is not required.

• Describe basic terminology and core concepts underlying artificial intelligence, machine learning, deep learning, and generative AI.
• Identify common algorithms and data types used to train AI and machine learning systems.
• Explore real-world applications of AI and ML across fields such as natural language processing, computer vision, and automation.
• Discuss key AWS services, such as Amazon SageMaker and Amazon Bedrock, and their roles in the AI ecosystem.
• Reflect upon foundational principles needed for advanced topics like prompt engineering, security, and responsible AI.