AWS AI/ML Services Integration
Description
Comprehensive integration of AWS AI/ML services including Comprehend, Rekognition, Transcribe, Textract, and other managed AI services with ML workflows.
Learning Objectives
Learners will master integration of AWS managed AI services for various use cases including natural language processing, computer vision, speech recognition, and document analysis. They will understand service capabilities, API integration patterns, cost optimization strategies, and how to combine multiple AI services for comprehensive solutions. Students will learn to implement end-to-end solutions leveraging pre-trained models and custom integrations.
Topics (12)
Advanced Rekognition implementation including object and scene detection, facial analysis, celebrity recognition, text in images, custom labels, and video analysis.
Comprehensive Transcribe usage including batch and streaming transcription, speaker identification, custom vocabulary, medical transcription, and call analytics.
Advanced Textract implementation including text extraction, form data extraction, table processing, handwriting recognition, and document workflow automation.
Comprehensive Translate usage including text translation, custom terminology, formality settings, batch translation, and integration with content management systems.
Advanced Polly implementation including voice selection, SSML usage, lexicon customization, neural voices, and real-time speech generation for applications.
Comprehensive Lex implementation including intent design, slot filling, dialog management, integration with Lambda, and multi-channel deployment for conversational AI.
Advanced Forecast implementation including dataset preparation, predictor training, forecast generation, and integration with business planning systems.
Comprehensive Personalize implementation including dataset preparation, solution creation, campaign deployment, and real-time recommendation integration.
Advanced integration patterns including service orchestration, data flow design, error handling, and architectural patterns for multi-service AI applications.
Comprehensive cost optimization including usage analysis, pricing model selection, caching strategies, and architectural optimization for AI service cost reduction.
Advanced application development including requirement analysis, service selection, architecture design, implementation, and deployment of complete AI-powered solutions.
Comprehensive Comprehend usage including sentiment analysis, named entity recognition, key phrase extraction, custom entity recognition, and document classification.