AWS Certified Generative AI Developer (AIP-C01) Prep

A practical guide to evaluating and selecting the right FM for your use case, including model parameters and providers.

Hands-on session to invoke a model, parse the response, and handle errors using the AWS SDK.

We'll walk through deploying a model from Hugging Face or your own training job to a SageMaker endpoint.

Analyze a real-world scenario for a marketing content generator, covering prompt engineering and basic guardrails.

Learn zero-shot, few-shot, and chain-of-thought prompting with downloadable templates you can use immediately.

A focused session on techniques to reduce hallucinations, including citation requirements and source grounding.

Deep dive into temperature, top_p, and max_tokens to control model output for different applications.

A practical look at how AWS versions its models and how to correctly reference them in your code and IaC.

Apply what you've learned by building a chatbot that can understand both text and images using Bedrock.

Learn how to manage and forecast costs for model invocation, training, and hosting on AWS.

We'll design a full RAG pipeline, from document ingestion with OpenSearch to retrieval and generation.

A practical session on processing your documents, choosing chunk sizes, and storing embeddings effectively.

Learn how to use Amazon Bedrock Agents to orchestrate multi-step tasks and integrate with external APIs.

Analyze the architecture for a secure, internal knowledge base using RAG and IAM-based access controls.

A problem-solving session to help you choose the right approach for your specific business problem.

A detailed walkthrough of preparing a training dataset and starting a fine-tuning job in SageMaker.

Learn the key metrics for RAG, including retrieval accuracy and faithfulness, with downloadable evaluation sheets.

A deep dive into IAM policies for Bedrock and SageMaker, ensuring least-privilege access for your applications.

Hands-on guide to using AWS native tools to detect and filter sensitive information in prompts and responses.

We'll use CodePipeline and SageMaker to automate the testing and deployment of a new model version.

Set up CloudWatch alarms and custom metrics to detect when your model's performance starts to degrade.

A focused session on building resilient applications that can handle Bedrock API limits gracefully.

Learn how to configure auto-scaling for your model endpoints to handle variable traffic loads.

Walk through the architecture for a model that runs in your VPC with no public internet access.

Implement Amazon Bedrock Guardrails to filter topics and deny unwanted content in your app's responses.

A comprehensive checklist covering IAM, VPC, data encryption, and prompt security for your projects.

Learn to build complex, multi-step GenAI workflows using Step Functions to coordinate different services.

A practical discussion on balancing latency, cost, and accuracy for production-grade GenAI systems.

Test your knowledge with a timed quiz focused on model selection, deployment, and pricing. Includes detailed answer explanations.

A second timed quiz covering RAG architecture, data ingestion, and agent implementation. We'll review the answers together.

The final practice exam, focusing on security best practices, monitoring, and deployment strategies.

A full-length mock exam to simulate the real test environment. We'll review strategies for pacing and tricky questions.

A review of the most commonly missed question types and concepts on the AIP-C01 exam.

A rapid-fire review of the most important AWS CLI commands and service limits you need to memorize.

What to do after you pass: building a portfolio, contributing to projects, and specializing in GenAI.

A step-by-step guide to moving from a prototype to a production-ready application, focusing on the AWS Well-Architected Framework.

A curated list of blogs, newsletters, and AWS re:Invent sessions to keep your skills sharp after the exam.

A final message from the instructor, plus a guide on how to claim your CPE credits and share your achievement.

A last-minute checklist to ensure you're prepared for exam day, from technical setup to mental readiness.

A summary of the entire course, highlighting the core concepts and practical skills you've gained.