Module C: Cloud Admin, Architect & AI

Module C: Cloud Admin, Architect & AI

1. AWS Solutions Architect Associate

    • Chapter 1: Introduction to AWS and Cloud Computing
    • Chapter 2: Identity and Access Management (IAM)
    • Chapter 3: Virtual Private Cloud (VPC)
    • Chapter 4: Compute Services
    • Chapter 5: Storage Services
    • Chapter 6: Databases and Data Management
    • Chapter 7: High Availability and Fault Tolerance
    • Chapter 8: Networking Essentials
    • Chapter 9: Security, Identity, and Compliance
    • Chapter 10: Monitoring and Optimization
    • Chapter 11: Application Services and Serverless Architectures
    • Chapter 12: AWS Architecture Best Practices

2. Azure Administrator

    • Chapter 1: Introduction to Microsoft Azure
    • Chapter 2: Managing Azure Subscriptions and Resources
    • Chapter 3: Implementing and Managing Storage
    • Chapter 4: Configuring and Managing Virtual Networks
    • Chapter 5: Deploying and Managing Azure Virtual Machines (VMs)
    • Chapter 6: Managing Azure Identities and Governance
    • Chapter 7: Managing and Securing Azure Storage
    • Chapter 8: Configuring and Managing Virtual Networks
    • Chapter 9: Monitoring and Managing Azure Resources
    • Chapter 10: Configuring and Managing Hybrid Connectivity
    • Chapter 11: Managing Azure Governance and Compliance

3. AWS DevOps Associate

    • Chapter 1: AWS CloudFormation and Infrastructure Automation
    • Chapter 2: Continuous Integration (CI) on AWS
    • Chapter 3: Continuous Delivery and Deployment (CD)
    • Chapter 4: Monitoring and Logging
    • Chapter 5: Security Automation and Compliance
    • Chapter 6: Web Hosting and Deployment
    • Chapter 7: Introduction to Web Application Development
    • Chapter 8: High Availability, Fault Tolerance, and Disaster Recovery
    • Chapter 9: Configuration Management and Automation
    • Chapter 10: Microservices and Containerization
    • Chapter 11: Serverless Application Deployment
    • Chapter 12: Performance Tuning and Cost Optimization
    • Chapter 13: Capstone Project

4. AWS - AI Practitioner

  • Introduction to Artificial Intelligence & AWS
    • Chapter 1: Overview of Artificial Intelligence (AI) & Machine Learning (ML)
    • Chapter 2: Introduction to AWS AI & ML Services
    • Chapter 3: AWS Machine Learning Stack
  • AI Model Deployment on AWS
    • Chapter 1: Model Training and Optimization
    • Chapter 2: Deploying AI Models with SageMaker
    • Chapter 3: Using AWS Lambda with AI Models
  • Security and Ethics in AI
    • Chapter 1: Security Best Practices for AI on AWS
    • Chapter 2: Ethical Considerations in AI
  • Data Processing and AI Workflows
    • Chapter 1: AWS Data Pipeline and Glue for AI
    • Chapter 2: AWS Kinesis for Real-time Data Streams
    • Chapter 3: Using Amazon Athena and Redshift for AI Data
  • Capstone Project
    • Chapter 1: Capstone Project Overview
    • Chapter 2: Building and Deploying the Solution
    • Chapter 3: Presentation and Evaluation

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