Lesson 1: Introduction to AWS AI
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Overview of AWS AI Services - Machine Learning with AWS, Key Benefits of AWS AI, Use Cases
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Core Concepts - Artificial Intelligence vs Machine Learning vs Deep Learning, Data Preparation Basics, AI Workflow in AWS
Lesson 2: Data Preparation for AI
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Data Collection and Storage - Using Amazon S3 for Data Storage, AWS Glue for Data Integration, Best Practices for Structured and Unstructured Data
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Data Cleaning and Transformation - Data Cleaning Tools: AWS DataBrew, Handling Missing or Corrupt Data
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Data Annotation - Amazon SageMaker Ground Truth, Creating Labeling Jobs
Lesson 3: AI-Powered Personalization
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Introduction to Amazon SageMaker - Features and Benefits, SageMaker Studio Overview
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Machine Learning Models - Supervised Learnin, Unsupervised Learning, Reinforcement Learning
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Model Development Lifecycle - Training, Validation, and Testing, Deploying Models with SageMaker
Lesson 1: AWS Pre-trained AI Services
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Natural Language Processing (NLP) - Amazon Comprehend, Use Cases: Sentiment Analysis, Topic Modeling
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Computer Vision - Amazon Rekognition, Use Cases: Image and Video Analysis
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Text and Speech Services - Amazon Polly for Text-to-Speech, Amazon Transcribe for Speech-to-Text
Lesson 2: Building Conversational AI
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Introduction to Amazon Lex - Key Features, Creating Chatbots
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Integration with Other AWS Services - Integrating with Lambda Functions, Deploying Chatbots via Amazon Connect,
Lesson 3: AI-Powered Personalization
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Amazon Personalize Overview - Features and Benefits, Recommendation Systems
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Workflow of Amazon Personalize - Data Import and Preparation, Model Training and Evaluation
Section 1: Custom Machine Learning Models
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Training Custom Models - Using Custom Datasets, Hyperparameter Optimization
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Advanced Deployment Strategies - Model Hosting and Monitoring with SageMaker, A/B Testing and Canary Deployments
Section 2: AI Ethics and Governance
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Responsible AI Practices - Bias Detection and Mitigation, Explainability in AI Models
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Security and Compliance - Data Encryption with AWS Key Management Service (KMS), GDPR and HIPAA Compliance
Section 3: Scaling and Optimizing AI Workloads
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Scaling AI Models - Using Amazon EC2 Spot Instances, Elastic Load Balancing
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Cost Optimization - AWS Cost Explorer, Reserved Instances for ML Training

- CategoryCloud Computing
- LevelIntermediate
- Duration3 Months
- Available SeatsUnlimited
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Real-Time Experts
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