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AWS GenAI Developer Pro AIP-C01 Exam 2026
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630 students

AWS GenAI Developer Pro AIP-C01 Exam 2026

Mastering Agentic Workflows: Build Intelligent Agents, RAG Pipelines, and Guardrails to Pass the AWS GenAI Professional
Created byCertification Expert
Last updated 2/2026
English

What you'll learn

  • Architect and deploy GenAI applications using Amazon Bedrock to invoke, stream, and manage Foundation Models like Claude, Llama, and Amazon Titan.
  • Build advanced RAG pipelines by integrating Knowledge Bases for Bedrock with vector stores like OpenSearch Serverless and Aurora pgvector for dynamic context.
  • Develop autonomous AI Agents that utilize Action Groups and Lambda functions to execute real-world tasks and orchestrate multi-step business workflows.
  • Implement Responsible AI governance using Bedrock Guardrails to filter PII and toxic content, while optimizing model performance and infrastructure costs.

Included in This Course

390 questions

  • AWS GenAI Developer PART 165 questions
  • AWS GenAI Developer PART 265 questions
  • AWS GenAI Developer PART 365 questions
  • AWS GenAI Developer PART 465 questions
  • AWS GenAI Developer PART 565 questions
  • AWS GenAI Developer PART 665 questions

Description

Bridge the gap between AI theory and production-grade applications with the most comprehensive prep guide for the AWS Certified Generative AI Developer - Professional (AIP-C01) exam.

Generative AI is moving from experimental "chatbots" to mission-critical enterprise systems. The AIP-C01 is the premier professional-level credential for developers who can architect, secure, and scale these solutions on the world’s leading cloud platform. This course is designed to take you deep into the Amazon Bedrock and SageMaker ecosystems, focusing on the real-world integration of Foundation Models (FMs) into scalable software architectures.

Rather than just focusing on prompt engineering, we dive into the "Plumbing of AI"—building robust Retrieval-Augmented Generation (RAG) pipelines, orchestrating multi-step Agents, and implementing enterprise-grade Guardrails to ensure safety and compliance.

What You Will Master:

  • Model Orchestration: Master Amazon Bedrock to invoke, stream, and manage models like Claude 3.5, Llama 3, and Amazon Titan.

  • Advanced RAG Pipelines: Build "long-term memory" for your AI using Knowledge Bases for Bedrock and vector databases like Amazon OpenSearch Serverless and Aurora pgvector.

  • Agentic Workflows: Create Agents for Amazon Bedrock that don't just talk, but act by executing API calls and Lambda functions to complete complex tasks.

  • Responsible AI & Governance: Implement Guardrails for Bedrock to filter toxic content and PII, and use AWS PrivateLink to ensure your data never leaves the AWS network.

  • Performance & Optimization: Compare models using Model Evaluation and optimize costs using Provisioned Throughput for high-demand production workloads.

Why Choose This Course?

  • Professional-Level Depth: We move beyond the basics, focusing on the architectural trade-offs between latency, cost, and accuracy.

  • 100% Scenario-Based: Every module mirrors the "Professional" exam style—presenting a business problem and requiring you to choose the most efficient AWS solution.

  • 2026 Curriculum Ready: Updated for the latest features, including Bedrock Data Automation, advanced Custom Model fine-tuning, and the latest Titan model family updates.

By the end of this course, you will be prepared to lead AI initiatives at the highest level, transforming businesses with secure, scalable, and intelligent Generative AI applications.

Who this course is for:

  • You have at least 2 years of experience building applications on AWS. You are proficient in Python and comfortable with serverless architectures (Lambda, API Gateway). You want to learn how to integrate Foundation Models (FMs) into real-world business workflows using Amazon Bedrock.

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