AWS AI Training with Certification

SKU: 2181
9 Lesson
|
30 Hours
igmGuru offers the best AWS AI training online worldwide. This comprehensive Amazon AWS AI course covers key topics such as building and deploying AI and machine learning models, leveraging AWS services like SageMaker, Rekognition, Comprehend, and Lex, and implementing AI solutions at scale. These Amazon AI course modules are designed by our industry experts with over 15 years of experience. Enroll in the AWS AI Training today to master AWS artificial intelligence services and advance your career in cloud-based AI and machine learning. After this course completion, person can appear for the latest AWS AI Certification Exam and become certified.

Amazon AI Course Overview

AWS AI Training covers tools, services, and frameworks offered by Amazon Web Services for building intelligent applications. Gain hands-on experience in machine learning, natural language processing, computer vision, and AI model deployment using AWS SageMaker, Lex, Polly, Rekognition, and more.

Prerequisites

What You Will Learn

  1. Fundamentals of Artificial Intelligence (AI) and its applications - Core AI/ML concepts, supervised vs. unsupervised learning, neural networks, and real-world industry applications — with a focus on how 2026's agentic AI era changes how AI is built and deployed.
  2. Hands-on with AWS AI services: SageMaker, Rekognition, Comprehend, Lex, Polly, Transcribe, Bedrock, Amazon Quick, and Amazon Connect expanded into four agentic AI solutions covering supply chain, hiring, and customer experience.
  3. Build, train, and deploy AI models with SageMaker - End-to-end model lifecycle on SageMaker from data prep to training to deployment.
  4. Implement computer vision with Rekognition - Image and video analysis, facial recognition, object detection, and content moderation using Amazon Rekognition.
  5. Perform NLP tasks with Comprehend - Text classification, entity recognition, sentiment analysis, and key phrase extraction using Amazon Comprehend integrated with Bedrock for generative NLP pipelines.
  6. Create chatbots with Lex - Design and deploy intelligent chatbots with Amazon Lex.
  7. Use Polly and Transcribe for speech AI - Text-to-speech and speech-to-text pipelines with Amazon Polly and Transcribe. Includes AgentCore Runtime's new bidirectional streaming for natural voice conversations.
  8. Generative AI Development with Amazon Bedrock - Build production-grade GenAI apps using Bedrock's model library like Claude, Amazon Nova, Meta Llama, Mistral, and more. Covers RAG pipelines, prompt engineering, fine-tuning with Nova Forge, and Amazon Bedrock Managed Agents powered by OpenAI.
  9. Amazon Nova AI Models - Dedicated module on Amazon's own model family — Nova Lite, Nova Pro, and Nova Premier
  10. Amazon Bedrock AgentCore - Build and Deploy AI Agents with the biggest new addition. AgentCore is a platform for building, deploying, and operating AI agents securely
  11. AgentCore Payments: Autonomous Agent Transactions - AgentCore Payments enables AI agents to autonomously access and pay for APIs, MCP servers, web content, and other agents
  12. Kiro: Agentic IDE for Developers - Kiro guides developers from prompt to feature with step-by-step guidance
  13. AWS Trainium3 and AI Infrastructure - Trainium3 UltraServers deliver up to 4.4× more compute performance, 4× greater energy efficiency, and nearly 4× more memory bandwidth than Trainium2
  14. Amazon S3 Vectors - AI-Native Storage S3 Vectors eliminates the need for a separate vector database for most AI use cases, cutting storage costs by up to 90%.
  15. Responsible AI practices: ethics, fairness, and data security - Ethics, fairness, data security, and compliance updated for the agentic era.

What’s New in AWS AI (2026)

  • Amazon Nova AI Models
  • Advanced AI Agents and Automation
  • Generative AI Development with Amazon Bedrock
  • OpenAI Integration with AWS
  • Improved SageMaker AI Capabilities
  • New AI Infrastructure and AI Chips
  • Next-Generation AI Inference Systems

Key Features

Course Curriculum

1. Fundamentals of Artificial Intelligence (AI)
2. Key AI concepts and terminology
3. Real-world AI use cases
1. Introduction to AWS AI ecosystem
2. Overview of key services: SageMaker, Rekognition, Comprehend, Lex, Polly, Transcribe, Bedrock
1. Basics of building, training, and deploying AI models
2. Using pre-built models and AutoML features
3. Integrating SageMaker with other AWS services
1. Image and video analysis
2. Object and facial recognition
3. Content moderation use cases
1. Sentiment analysis, entity recognition, and topic modeling
2. Text analytics and insights
3. Language detection and custom NLP models
1. Building chatbots and virtual assistants
2. Intent and slot management
3. Integration with web and mobile applications
1. Text-to-speech synthesis with Polly
2. Speech-to-text conversion with Transcribe
3. Real-time and batch processing
1. Introduction to generative AI models
2. Use cases for text, image, and code generation
3. Building generative AI solutions using AWS services
1. Ethical considerations in AI deployment
2. Fairness, accountability, and transparency
3. Data privacy and security in AI applications
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Course Fees

Online Class Room Program

US $ 799.00
100% Money Back Guarantee
  • Duration : 30 Hrs
  • Plus Self Paced

Classes Starting From

  • Fast Track Batch 08 Jun 2026
  • Weekday Batch 08 Jun 2026
  • Weekend Batch 13 Jun 2026

Corporate Training

Corporate Training
  • Customized Training Delivery Model
  • Flexible Training Schedule Options
  • Industry Experienced Trainers
  • 24x7 Support

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AWS AI Certification

Official Certification Name: AWS Certified AI Practitioner - AIF-C01

Exam Format:

  • Duration: 90 minutes
  • Number of Questions: 65 multiple-choice/multiple-response questions
  • Passing Score: 70% (may vary slightly)
  • Type: Scenario-based and concept-based multiple-choice questions
  • Validity: 3 years from the date of certification
  • Cost: $100 USD

Upon successful completion of the AWS AI Training, learners will earn an AWS AI Course Completion Certificate from igmGuru. This certification validates your expertise in AWS AI services, machine learning model development, AutoML, data processing, and cloud-based AI deployment. These certificates have lifetime validity. To earn this certification, you need to enroll in the AWS AI Training Course and fulfill the minimum requirements.

AWS AI Certification

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