AWS Artificial Intelligence Practitioner
Gain hands-on skills in AI, ML, and GenAI with AWS tools that drive real-world innovation.
Duration
4 weeksWeekly study
3 hoursLanguages
English, Italiano, Español, Français, PortuguêsEnglish, Italiano, EspañolDigital upgrade
Free
AWS Artificial Intelligence Practitioner
This course has been certified by the CPD Certification Service as conforming to continuing professional development principles. Find out more.
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Master AI and machine learning with AWS tools
Discover how artificial intelligence is transforming industries with this practitioner-level AWS course.
Through interactive lessons, real-world case studies, and expert insights, you’ll build the foundational knowledge and practical skills to work confidently with AI and ML technologies using AWS tools and services.
Explore the core concepts of AI, ML and GenAI
You’ll get an overview of artificial intelligence and machine learning, exploring the differences between AI, ML, deep learning, and generative AI.
Understand common algorithms and learn foundational terms and the types of data used to train AI models through use cases across NLP, computer vision, and business automation.
Apply AWS services to build AI-powered solutions
Then, learn how to build and deploy AI models using AWS services, like Amazon SageMaker and Amazon Bedrock. You’ll discover how to define use cases, train and evaluate models, and manage lifecycles using MLOps.
You’ll explore how to apply fine-tuning techniques and deploy scalable AI solutions tailored to real business problems.
Build responsible, secure, and explainable AI systems
Finally, you’ll delve into the principles of responsible AI. This includes fairness, transparency, and human-centred design.
You’ll learn how to protect data privacy, reduce model bias, and align with governance frameworks, as well as gain experience with AWS tools for security, compliance, and prompt engineering. With this insight, ensuring your AI systems are ethical, compliant, and secure will be that much more possible.
By the end of this course, you’ll walk away with practical tools, real-world experience, and an understanding of AI/ML implementation best practices so you’re ready to innovate and lead in your organisation.
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 AI Practices and developing ML solutions
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.
Developing ML Solutions
In this machine learning section, you will learn about the machine learning lifecycle, and how to use AWS services at every stage.
Machine Learning Models Performance Evaluation
In this activity, you will learn about model evaluation. You will look at which metrics can be used for two very common ML algorithms: classification and regression.
Fundamental Concepts of MLOps
MLOps combines people, technology, and processes to deliver collaborative ML solutions.
Weekly Wrap-up
We conclude and discuss this week's learning.
Week 3
Developing Gen AI Solutions and Optimising Foundation Models
Developing Generative AI Solutions
In this activity, you will explore the generative artificial intelligence (generative AI) application lifecycle.
Improving the Performance of an FM
After selecting an appropriate pre-trained foundation model that aligns with the business use case, the next step is to focus on improving the performance of the model.
Optimising Foundation Models
In this activity, you will explore two techniques to improve the performance of a foundation model (FM): Retrieval Augmented Generation (RAG) and fine-tuning.
Optimising a Foundational Model with Fine-Tuning
In this activity you will look at a case study: AnyCompany.
Conclusion
You’ll reinforce your understanding of Transformers and their role in shaping the future of artificial intelligence.
Week 4
Security, Compliance, Governance for AI Solutions and Essentials of Prompt Engineering
Security, Compliance, and Governance for AI Solutions
Amazon Web Services (AWS) provides a comprehensive set of tools, services, and partner solutions to build and secure artificial intelligence (AI) systems.
Securing AI Systems
In the context of AI and generative AI, there are a number of security tasks, such as threat detection, vulnerability management, infrastructure protection, prompt injection, and data encryption.
Prompt Basics
In this topic, you will be introduced to the fundamentals of crafting effective prompts. You will gain an understanding of how to refine and optimise prompts for a range of use cases.
Risks
This activity will provide you with an understanding of how FMs handle prompt misuses or risks.
Who is this accredited by?
The CPD Certification Service was established in 1996 and is the leading independent CPD accreditation institution operating across industry sectors to complement the CPD policies of professional and academic bodies.
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...
- Explain core concepts of artificial intelligence, machine learning, and generative AI, including natural language processing and computer vision.
- Differentiate among AWS AI/ML services and tools (e.g., Amazon SageMaker, Amazon Bedrock) and their appropriate use cases.
- Apply AI/ML workflows within the AWS console, including data preparation, model training, deployment, and monitoring.
- Evaluate real-world scenarios to determine the most suitable AI/ML solutions leveraging AWS technologies.
Who is the course for?
This course is for any learners interested in AI and ML, including developers, analysts, and business professionals with a basic understanding of AWS services and AI/ML concepts.
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.
Endorsers and supporters
supported by
What's included?
Amazon Web Services (AWS) are offering everyone who joins this course a free digital upgrade, so that you can experience the full benefits of studying online for free. This means that you get:
Learning on FutureLearn
Your learning, your rules
- Courses are split into weeks, activities, and steps to help you keep track of your learning
- Learn through a mix of bite-sized videos, long- and short-form articles, audio, and practical activities
- Stay motivated by using the Progress page to keep track of your step completion and assessment scores
Join a global classroom
- Experience the power of social learning, and get inspired by an international network of learners
- Share ideas with your peers and course educators on every step of the course
- Join the conversation by reading, @ing, liking, bookmarking, and replying to comments from others
Map your progress
- As you work through the course, use notifications and the Progress page to guide your learning
- Whenever you’re ready, mark each step as complete, you’re in control
- Complete 90% of course steps and all of the assessments to earn your certificate
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