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AWS Certified Generative AI Developer - Professional - Printable Version +- Nice1 Community Forum (https://talk.nice1.org) +-- Forum: Nice1 Community (https://talk.nice1.org/forumdisplay.php?fid=3) +--- Forum: Media (https://talk.nice1.org/forumdisplay.php?fid=9) +--- Thread: AWS Certified Generative AI Developer - Professional (/showthread.php?tid=3107) |
AWS Certified Generative AI Developer - Professional - Courses2025 - 01-28-2026 ![]() Free Download AWS Certified Generative AI Developer - Professional Published 1/2026 Created by Rahul Trisal MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch Level: All | Genre: eLearning | Language: English | Duration: 104 Lectures ( 10h 3m ) | Size: 6.1 GB Focused 10-hr exam prep: Bedrock, RAG, AI Agents & scenario-based architecture-driven trade-offs | 40+ hands-on demos What you'll learn ✓ Pass the AWS Certified Generative AI Developer - Professional (AIP-C01) exam by mastering architecture decisions and trade-offs. ✓ Master architecture decisions for production GenAI systems on AWS - the core skill tested on the exam. ✓ Evaluate trade-offs between cost, latency, accuracy, and scale in real-world GenAI scenarios. ✓ Think like the AWS exam expects - analyzing scenarios and choosing the best architectural approach. Requirements ● Basic AWS knowledge (IAM, S3, Lambda) Description A Different Approach to GenAI Certification Prep The AWS Certified Generative AI Developer - Professional (AIP-C01) exam is a tricky, scenario-based certification. It's not about bullet-point memorization. It tests your ability to make architecture decisions and trade-offs across real-world generative AI systems. That is exactly how this course is designed. • 10 hours. Laser-focused. • Built around how the exam actually tests you - scenarios, trade-offs, and multi-layered architecture decisions. • I designed this course after passing the AIP-C01 exam myself, intentionally moving away from 20+ hour "comprehensive" courses that prioritize coverage over clarity. What Makes This Course Different • Architecture-First Learning - Every concept is taught through the lens of production design decisions, not isolated feature walkthroughs • Two Complete Projects - Build a GenAI Equipment SME Assistant (15 architecture decisions) and a RAG-powered E-Learning Q&A system (10 architecture decisions) • Exam-Realistic Practice - 40+ scenario-based quiz questions + mini mock exam written in AWS exam style. Quiz questions at Professional-level difficulty focused on decision-making, not recall. Quality over quantity. • Hands-On Mastery - 40+ demos of the most complex concepts, so you learn by building, not by watching slides • Respects Your Time - 10 hours of focused content. No filler. No irrelevant lectures. Course Contents • 10 hours of focused video content • 40+ hands-on demos covering complex, real-world scenarios • 40+ exam-style questions across topic quizzes • Mini mock exam to test your readiness • 300+ structured slides aligned to architecture decisions • 2 complete projects with production architecture walkthroughs • Backed by Udemy's 30-day money-back guarantee. What You'll Be Able to Design, Evaluate, and Decide This course prepares you to think and decide like the AWS exam expects - by evaluating trade-offs across real-world generative AI architectures. Designing GenAI Applications with Amazon Bedrock You'll learn how to make the right architectural choices when building GenAI applications on AWS, including • Choosing the right foundation model based on accuracy, latency, cost, and use case constraints • Tuning inference parameters, provisioned throughput, and capacity for production workloads • Applying guardrails, content filters, and Responsible AI controls to meet safety and compliance requirements • Observability and Monitoring • Model customization: distillation, fine-tuning, and continued pre-training • Model evaluation using programmatic metrics, LLM-as-a-Judge, and human review Architecting Retrieval Augmented Generation (RAG) Systems You'll design end-to-end RAG pipelines and understand the trade-offs behind each decision, including • Selecting and preparing data sources for retrieval-based architectures • Choosing chunking strategies, embeddings, and vector databases based on recall, precision, and scale • Optimizing retrieval using reranking, hybrid search, and evaluation techniques • Implementing Amazon Bedrock Knowledge Bases for managed RAG solutions Building Agentic AI Systems on AWS You'll move beyond single-prompt LLM applications and design agent-based systems, including • Architecting workflows with Amazon Bedrock Agents • Integrating tools and context using the Model Context Protocol (MCP) • Deploying and operating agents using Amazon Bedrock AgentCore Who This Course Is For - AWS developers preparing for the AIP-C01 certification - Cloud architects adding generative AI to their skillset - Busy professionals who want focused, efficient exam preparation - Engineers who learn better through architecture reasoning than feature memorization Requirements • Basic AWS knowledge (IAM, S3, Lambda) • Familiarity with REST APIs and JSON • AWS account for hands-on labs (Free Tier eligible) • No prior AI/ML experience required Who this course is for ■ AWS developers and architects preparing for the AIP-C01 (Generative AI Developer - Professional) certification exam. ■ Engineers who learn better through architecture reasoning and trade-off analysis than feature memorization. ■ Busy professionals who want focused, efficient exam preparation - not 20+ hours of content. 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