This course is part of the AWS AI Practitioner - Foundational Professional Certificate
AWS Fundamentals of Machine Learning and Artificial Intelligence
Explore the foundations of AI, machine learning, and generative AI, and discover how AWS supports real-world use cases.
Duration
2 weeksWeekly study
3 hours100% online
How it worksIncluded in a Professional Certificate
Course 1 of 4
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.
Syllabus
Week 1
Fundamentals of Machine Learning and Artificial Intelligence
Fundamentals of Machine Learning and Artificial Intelligence
In this activity, you will gain a solid baseline understanding of AI and ML, along with the terminology and principles that will support your continued learning journey.
AWS Infrastructure and Technologies
AWS offers a comprehensive suite of ML and generative AI services that can help you unlock the full potential of these transformative technologies.
Artificial Intelligence
In this activity, you will explore real-world use cases in artificial intelligence (AI), machine learning (ML), and generative artificial intelligence (generative AI) across a range of industries.
Machine Learning
In this activity, you will learn about when ML is an appropriate solution and the techniques used for specific use cases.
Generative AI
In this activity, you will learn about the capabilities and challenges of AI, the factors to consider when selecting a generative AI model, and the business metrics for generative AI applications.
Week 2
Responsible Artificial Intelligence Practices
Welcome to Week Two
This activity will cover what we will learn in the upcoming week
Introduction to Artificial Intelligence practices
Responsible AI refers to practices and principles that ensure that AI systems are transparent and trustworthy while mitigating potential risks and negative outcomes.
Developing Responsible AI systems
As the leader in cloud technologies, AWS offers services like Amazon SageMaker and Amazon Bedrock that have built-in tools to help you with responsible AI.
Transparent and Explainable AI Models
To promote trust and accountability in an AI system, there should be transparency and explainability in the model.
Weekly Wrap-up
We conclude and discuss this week's learning.
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Learning on this course
On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.
What will you achieve?
By the end of the course, you‘ll be able to...
- 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.
Who is the course for?
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.
Who developed the course?
Amazon Web Services (AWS)
AWS is the world’s most comprehensive cloud, enabling organizations to accelerate innovation, reduce costs, and scale more efficiently.
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