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Generative AI Essentials on AWS (AIF-C01)
Your AI use cases need suitable services and evaluated results. With AWS, connect data, models and integration to understand the technical options more clearly. Develop reference points for designing experiments and assessing implementation conditions.
- Duration
- 1 day 7 hours
- Code
- AWS06EN Code
- Certification
- AWS Certified AI Practitioner Certification
Accredited training for the AWS Certified AI Practitioner certification.
Presentation
Generative artificial intelligence is profoundly transforming business practices. AWS offers a complete ecosystem of AI services to design, deploy and govern innovative solutions:
Amazon Bedrock for access to foundation models, Amazon Q Developer for development assistance, and Amazon SageMaker AI for machine learning. These tools enable organisations to accelerate AI projects while managing risk and compliance.
This one-day course provides practical skills to understand and apply generative AI on AWS. It covers the 5 official AIF-C01 exam domains: AI and machine learning fundamentals, generative AI principles, foundation model applications, guidelines for responsible AI, and AI solution security, compliance and governance. Through practical Amazon Bedrock workshops, you will learn to design effective prompts, evaluate results and plan AI projects.
By the end of the day, you will have the knowledge to identify appropriate business use cases for generative AI and be ready to take the official AIF-C01 exam, included in our offer, to obtain AWS Certified AI Practitioner - Foundational certification (see the certification tab for more information).
As a premium training partner (ATP) accredited by Amazon Web Services, Oo2 offers skills development and certification courses that meet the organisation's rigorous quality standards.
Objectives
By the end of this Generative AI Essentials on AWS course, you will achieve the following skills objectives:
- Describe fundamental AI, machine learning and generative AI concepts, including LLMs, neural networks and agentic AI.
- Identify the right AWS tools and services for specific AI use cases: Amazon Bedrock, Amazon SageMaker AI and Amazon Q Developer.
- Design and optimise effective prompts using prompt engineering techniques on Amazon Bedrock.
- Evaluate and select foundation models suited to business needs, considering regulatory and operational constraints.
- Apply responsible AI principles: bias, fairness, transparency and explainability.
- Identify security, compliance and governance requirements for AWS AI solutions.
- Prepare for and pass AIF-C01 to obtain AWS Certified AI Practitioner - Foundational certification.
Program
Module 1: introducing generative AI on AWS
- Fundamental AI, machine learning and generative AI principles: LLMs, neural networks and agentic AI.
- Foundation models and their characteristics.
- AWS generative AI services: Amazon Bedrock, Amazon SageMaker AI and Amazon Q Developer.
- Comparing traditional ML models and foundation models against regulatory and operational constraints.
Module 2: exploring generative AI use cases
- Identifying appropriate business use cases for generative AI.
- Practical applications: content generation, summarisation, translation, coding assistance and conversational agents.
- Selecting the right AI tool for specific business needs.
Case study
- Analyse and discuss a concrete generative AI use case in a business context.
Module 3: mastering prompt engineering
- Prompt engineering fundamentals and best practices.
- Advanced prompting strategies: zero-shot, few-shot and chain-of-thought.
- Model parameters and token-based pricing.
Labs
- Optimise slogan generation with Amazon Bedrock by experimenting with different prompting techniques.
Module 4: implementing responsible AI practices
- Responsible AI fundamentals: bias, fairness, transparency and explainability.
- Generative AI-specific considerations: hallucinations, misinformation and copyright.
Labs
- Implement responsible AI principles using Amazon Bedrock guardrails.
Module 5: understanding security, governance and compliance
- AI solution security fundamentals: AWS IAM access management and data protection.
- Managing unwanted prompts and securing generative AI services.
- Governance and regulatory compliance principles for AI solutions on AWS.
Module 6: planning and deploying generative AI projects
- Defining a use case and selecting an appropriate foundation model.
- Performance improvement techniques: fine-tuning, RAG (Retrieval Augmented Generation) and results evaluation.
- Deploying a generative AI application on AWS.
- Introducing Amazon Q Business for business AI assistance.
Module 7: integrating AI into the development lifecycle
- Principles for integrating generative AI into software development workflows.
- Using Amazon Q Developer for development assistance and code generation.
Labs
- Create a complete project plan using generative AI on Amazon Bedrock.
Audience
This course is intended for anyone wishing to discover practical generative AI applications on AWS, regardless of technical background. The audience includes:
- Business professionals and analysts in marketing and sales, and product and project managers seeking to explore how generative AI can accelerate their activities and enrich their campaigns.
- IT technicians and IT managers wishing to assess generative AI's potential on AWS and identify relevant use cases for their organisation.
- Anyone wishing to obtain AWS Certified AI Practitioner - Foundational (AIF-C01) certification to validate their AI, machine learning and generative AI knowledge.
Prerequisites
This course has no technical prerequisites. It is open to anyone wishing to discover generative AI on AWS, regardless of their level of computer knowledge.
Teaching and assessment methods
- Initial skills assessment
- Training materials provided to participants
- Continuous assessment throughout the course
- End-of-course feedback questionnaire
- Combination of theory and practical application
- Attendance records
- Post-course follow-up evaluation
- Practical exercises
Course highlights
- AWS-accredited ATP partner: Oo2 is a premium training partner (ATP) accredited by Amazon Web Services, ensuring official content and AWS-certified trainers.
- Accessible training: no technical prerequisites are required, making this course an ideal introduction to generative AI on AWS for business and IT professionals.
- Practical Amazon Bedrock labs: experiment with prompt engineering and guardrails directly in real AWS environments to ground concepts in concrete use cases.
- AIF-C01 exam voucher included: an official AWS voucher code is provided at the end of the course so you can schedule your certification exam.
- A rapidly growing strategic subject: generative AI on AWS is one of the most sought-after business skills, helping you get ahead in your market.
Dates and sessions
Choose the date and delivery format that suit you.
No upcoming sessions are currently available.
AWS, Amazon Bedrock, Amazon Q Developer, Amazon Q Business, Amazon SageMaker and other AWS brands are registered trademarks of Amazon.com, Inc. or its affiliates.