What you'll learn

• Understand core concepts behind AI, Machine Learning and Deep Learning.
• Differentiate classical ML from Generative AI and foundation models.
• Identify when and how to use AWS AI services in real projects.
• Understand the end-to-end lifecycle of an AI solution on AWS.
• Apply Responsible AI principles: security, governance and bias awareness.

Who should attend?

This training is ideal for cloud engineers, architects, consultants, software engineers working with AI teams, product managers, technical trainers and professionals transitioning into AI-focused roles. No heavy math or unnecessary theory—just clear AI fundamentals explained for technical minds.

Prerequisites

• No coding or data science background required.
• No prior AWS certification required.
• Basic cloud knowledge is useful but not mandatory.

Course curriculum

Module 1 – AI & Machine Learning fundamentals

What AI means in production environments, supervised vs unsupervised learning, strengths, limitations and risks of AI systems.

Module 2 – Machine Learning on AWS

ML lifecycle: data → training → inference, core concepts behind Amazon SageMaker, evaluation, performance and cost considerations.

Module 3 – Generative AI on AWS

How Generative AI and foundation models work, Amazon Bedrock and managed models, real use cases (text generation, summarisation, assistants).

Module 4 – AWS AI services in practice

Computer vision with Amazon Rekognition, NLP with Comprehend, Transcribe and Translate, choosing the right service for the right problem.

Module 5 – Responsible AI & governance

Security, compliance, data protection, bias, fairness, transparency and AWS best practices for responsible AI.

Module 6 – Certification readiness

Exam structure and question patterns, typical scenarios and traps, strategies to pass the AWS Certified AI Practitioner exam with confidence.

Certification exam

• Exam: AWS Certified AI Practitioner (AIF-C01).
• Format: Multiple-choice and multiple-response.
• Duration: 90 minutes.
• Language: English.
• Credential: Official AWS certification.

Why this certification matters

• Build solid AI literacy aligned with AWS standards.
• Collaborate confidently with ML engineers and data scientists.
• Understand Generative AI beyond the hype.
• Prepare for more advanced AWS AI and ML certifications.

What's next?

After this certification, learners typically progress to the AWS Certified Machine Learning – Specialty, advanced AI architecture and MLOps paths, or specialised Generative AI solution design on AWS.