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.
Homepage
Code:
Bitte
Anmelden
oder
Registrieren
um Code Inhalt zu sehen!
Recommend Download Link Hight Speed | Please Say Thanks Keep Topic Live
Code:
Bitte
Anmelden
oder
Registrieren
um Code Inhalt zu sehen!
