Lesson 1: AI Overview
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What is AI - Machines simulating intelligence
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AI vs ML vs DL - Learning vs logic vs layers
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AI Use Cases - Chatbots, vision, speech, recommendations
Lesson 2: AWS AI Services Overview
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Pre-trained AI Services - Vision, language, speech
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Access Methods - Console, CLI, SDKs, APIs
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Responsible AI (Brief) - Accuracy, privacy, fairness
Lesson 1: Computer Vision (Amazon Rekognition)
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Image Analysis - Labels, text, unsafe content
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Facial Analysis - Emotion, face match
Lesson 2: Natural Language Processing (Amazon Comprehend)
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Sentiment Detection - Positive, neutral, negative
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Entity Recognition - Names, places, dates
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Custom Classification - Domain-specific text tagging
Lesson 3: Speech AI (Amazon Transcribe & Polly)
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Transcribe Audio - Convert voice to text
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Synthesize Speech - Convert text to natural voice
Lesson 4: Conversational AI (Amazon Lex)
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Build a Chatbot - Intents, utterances, slots
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Multi-turn Dialogs - Dynamic responses
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Lex-Lambda Integration - Backend logic with AWS Lambda
Lesson 1: SageMaker Basics
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What is SageMaker - ML model building platform
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Autopilot - AutoML for training models
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Notebooks (Intro) - Cloud-hosted Jupyter
Lesson 2: Deployment & Inference
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Deploy Model - Real-time prediction endpoint
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Batch Inference - Large-scale scoring

- CategoryAWS
- LevelBeginner
- Duration3 Months
- Available SeatsUnlimited
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