AWS Certified Generative AI Developer Professional Exam Prep

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Free Download AWS Certified Generative AI Developer Professional Exam Prep
Published 11/2025
Created by Maruchin Tech,Maruchin Tech
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Expert | Genre: eLearning | Language: English | Duration: 265 Lectures ( 22h 6m ) | Size: 10.3 GB

Pass the NEW AWS Certified Generative AI Developer Professional (AIP-C01) Exam on Your First Try!
What you'll learn
Ace the Exam: Master all domains of the AWS Certified Generative AI Developer Professional exam and gain the confidence to pass on your first attempt.
Master Core GenAI Services: Gain advanced, practical skills in designing, developing, and deploying solutions using Amazon Bedrock and Amazon SageMaker.
Build the Full Ecosystem: Learn to integrate supporting AWS services for data processing, feature engineering, vector storage, and databases essential for GenAI
Implement Secure & Automated Pipelines: Confidently apply best practices for securing GenAI workloads (IAM, KMS, VPC) and automating the MLOps lifecycle .
Requirements
IT Professionals with AWS experience who want to specialize in Generative AI and validate their professional-level skills.
Description
[Course Description]Welcome to the most comprehensive prep course for the NEW AWS Certified Generative AI Developer - Professional exam.This course is meticulously designed for experienced developers who want to validate their advanced skills in designing, developing, deploying, managing, and securing Generative AI applications on the AWS cloud. This is a new, challenging, and highly in-demand certification, and this course will give you the knowledge and confidence you need to pass.We go far beyond just theory. This course provides a deep dive into the critical services and concepts you must know for this professional-level certification.[What You Will Master]In this course, you will gain hands-on expertise and deep technical knowledge across all exam domains:Core Generative AI Services: Master Amazon Bedrock, including foundational model selection, advanced prompt engineering, Retrieval Augmented Generation (RAG), agents, and fine-tuning. We also cover Amazon SageMaker in-depth, including SageMaker JumpStart, training, inference, and endpoints.Data Lifecycle & Pipelines: Learn to integrate essential data processing services (like AWS Lambda, AWS Glue), feature stores (Amazon SageMaker Feature Store), and specialized databases (like vector stores for OpenSearch or Amazon Aurora) to build robust data pipelines for your GenAI models.Security & Governance: Implement rock-solid security using IAM roles and policies, network isolation with VPCs, and data encryption with AWS KMS, ensuring your GenAI applications are secure and compliant.DevOps & Automation: Master the automation of your GenAI workflows using AWS CI/CD tools (like AWS CodePipeline and AWS CodeBuild) for seamless integration, deployment, and monitoring.[Course Agenda]This course is logically structured to build your knowledge from the ground up:Section 1: AWS Certification and Exam PreparationGet a complete overview of the AWS certification landscape, the specifics of the Generative AI Professional exam, and how to set up your AWS account for hands-on learning.Section 2: Fundamentals of AI and Machine LearningBuild a solid foundation by reviewing the basic terminology and core concepts of AI, ML, and Generative AI, including the complete ML pipeline.Section 3: Deep Dive into AWS ServicesThis is the core of the course. We will review all essential AWS services, category by category, as they relate to the exam.1. AI/ML: SageMaker, Bedrock, and other fully-managed services.2. Management & Governance: Organizations, Systems Manager, CloudWatch, Config, CloudTrail, CloudFormation.3. Security, Identity, Compliance: IAM, KMS, Secrets Manager, Macie.4. Storage: S3, EFS, EBS, Storage Gateway.5. Compute & Container: EC2, AutoScaling, ECS, EKS, Lambda, AWS Batch.6. Networking & Content Delivery: VPC, Firewall, CloudFront, DirectConnect.7. Database: RDS, Aurora, Redshift, DynamoDB, ElastiCache.8. Application Integration: API Gateway, SQS, SNS, EventBridge, StepFunctions, MWSS.9. Analysis: Lake Formation, Glue, Kinesis, Data Firehose, Apache Flink, Athena, EMR, OpenSearch, QuickSight.10. Developer: CodeBuild, CodeDeploy, CodePipeline.Section 4: Full-Length Practice TestTest your knowledge with a complete, original 75-question practice exam designed to simulate the real test environment.Section 5: SummaryWe'll wrap up the course with key takeaways and final tips for exam day.[Meet Your Instructor]Hello, I am Maruchin Tech.With a background spanning over a decade in technology, I've been working in major firms, including the Renault-Nissan-Mitsubishi Alliance, Accenture, and NTT Data.I have created +40 courses covering Cloud Computing, Programming, Python, and Machine Learning, which have reached +80,000 students on Udemy. As an IT consultant, I specialize in cloud computing solutions for leading corporations.I hold all currently available AWS certifications (12x AWS Certified), and I am passionate about sharing my knowledge with you.Join me in exploring the dynamic world of IT, where continuous learning and innovation open the door to endless possibilities. Let's embark on this journey together.This course is your complete guide to mastering the exam domains and earning one of the industry's most in-demand certifications.I look forward to seeing you in the course!
Who this course is for
Software Engineers and AI/ML Engineers responsible for designing, building, and maintaining Generative AI solutions on AWS.
Developers preparing to take and pass the new AWS Certified Generative AI Developer Professional exam.
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AWS Certified Generative AI Developer Professional Exam Prep
Published 12/2025
Duration: 3h 52m | .MP4 1920x1080 30fps(r) | AAC, 44100Hz, 2ch | 2.56 GB
Genre: eLearning | Language: English​

Your complete guide to the AWS GenAI Developer exam. Master Bedrock, SageMaker, and AI Services.

What you'll learn
- Build and orchestrate sophisticated GenAI applications using Amazon Bedrock Agents, Knowledge Bases, and Prompt Flows.
- Leverage Amazon SageMaker JumpStart to deploy, fine-tune, and manage foundation models for your specific use cases.
- Master the end-to-end ML lifecycle, including bias detection and model monitoring using Amazon SageMaker Clarify.
- Integrate pre-trained AI services like Amazon Rekognition, Textract, and Transcribe directly into your applications.

Requirements
- An active AWS account is required to perform the hands-on lab exercises.
- A solid understanding of core AWS services (IAM, S3, EC2, Lambda) is assumed.
- Basic familiarity with machine learning concepts (e.g., training vs. inference) is helpful but not strictly required.
- No prior experience with Amazon Bedrock or SageMaker is required; we will start from the basics.

Description
Generative AI is not just a buzzword-it is the biggest shift in software development in decades.

As organizations rush to adopt AI, the demand for developers who can build, secure, and deploy Generative AI applications on AWS has skyrocketed. TheAWS Certified Generative AI - Developercertification is the industry's gold standard for validating these cutting-edge skills.

But passing the exam-and actually building these applications-requires more than just reading documentation. You need practical, hands-on experience.

This course is your complete guide to mastering the AWS Generative AI stack.

Designed specifically for developers, this course bridges the gap between theory and real-world implementation. We strip away the complexity and focus on the practical"how-to"of building GenAI solutions.

You will master the following key domains through hands-on labs:

Amazon Bedrock Deep Dive:Go far beyond simple text generation. You will learn to build complex, agentic workflows usingBedrock Agents, implement Retrieval-Augmented Generation (RAG) usingKnowledge Bases, and engineer widely effective prompts usingPrompt ManagementandPrompt Flows.

Amazon SageMaker for Developers:You don't need to be a data scientist to use SageMaker. We focus on the developer-centric features, showing you how to useSageMaker JumpStartto deploy and fine-tune foundation models,SageMaker Clarifyto detect bias, andSageMaker Data Wranglerto prepare your data efficiently.

MLOps and Governance:Learn how to operationalize your models usingSageMaker Model MonitorandModel Registryto ensure your applications remain reliable in production.

AI Services:Integrate powerful, pre-trained AI capabilities into your apps usingAmazon Rekognition(computer vision),Amazon Textract(document extraction), andAmazon Transcribe(speech-to-text).

Who is this course for?

Software Developers looking to transition into AI/ML development.

Candidates preparing for theAWS Certified Generative AI - Developerexam.

Solutions Architects designing GenAI applications.

Anyone who wants to move beyond "Hello World" and build enterprise-grade AI solutions.

Don't get left behind.Enroll today and start building the future of software on AWS!

Who this course is for:
- Software Developers who want to build and integrate Generative AI applications on AWS.
- AWS Certification Candidates preparing for the AWS Certified Generative AI - Developer exam.
- Solutions Architects designing GenAI solutions using Amazon Bedrock and SageMaker.
- Machine Learning Engineers looking to leverage managed services like SageMaker JumpStart.
- Technical Leads who need to understand the capabilities of the AWS Generative AI stack.

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