Phase 1: Foundations of Cloud Computing
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Introduction to Cloud Computing
- What is Cloud Computing?
- History and evolution of cloud computing.
- Key characteristics: Scalability, On-Demand, Pay-As-You-Go.
- Cloud Service Models: IaaS, PaaS, SaaS.
- Deployment Models: Public, Private, Hybrid, and Community Cloud.
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Benefits and Challenges
- Cost efficiency, flexibility, global reach.
- Security, compliance, and latency concerns.
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Virtualization Basics
- What is virtualization?
- Virtual machines vs. containers.
- Role of hypervisors (Type 1 & Type 2).
Phase 2: Cloud Service Providers (CSPs)
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Top Cloud Providers Overview
- AWS (Amazon Web Services)
- Microsoft Azure
- Google Cloud Platform (GCP)
- IBM Cloud, Oracle Cloud, etc.
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Hands-On with AWS, Azure, and GCP
- Create free-tier accounts.
- Learn the dashboards and interfaces.
- Use basic services like EC2 (AWS), Virtual Machines (Azure), Compute Engine (GCP).
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Core Services Comparison
- Compute: EC2, Azure VM, Compute Engine.
- Storage: S3, Blob Storage, Cloud Storage.
- Networking: VPC, Virtual Network, Cloud Interconnect.
Phase 3: Core Cloud Services
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Compute
- Virtual Machines.
- Serverless Computing (AWS Lambda, Azure Functions, Google Cloud Functions).
- Auto-scaling and load balancing.
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Storage
- Object storage vs. Block storage vs. File storage.
- Cloud storage services like S3, Azure Blob, GCS.
- Backup and archival strategies.
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Networking
- Virtual Private Cloud (VPC).
- Load Balancers, Firewalls, DNS.
- Content Delivery Networks (CDNs) like CloudFront.
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Databases
- SQL: RDS (AWS), SQL Database (Azure), Cloud SQL (GCP).
- NoSQL: DynamoDB, Cosmos DB, Firestore.
- Data Warehousing: Redshift, Synapse Analytics, BigQuery.
Phase 4: Advanced Topics
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Cloud Security
- Identity and Access Management (IAM).
- Encryption (in-transit, at-rest).
- Security Groups, Firewalls, and VPNs.
- Compliance standards (GDPR, HIPAA).
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DevOps and Cloud
- Infrastructure as Code (IaC): Terraform, AWS CloudFormation.
- CI/CD Pipelines: Jenkins, GitHub Actions, AWS CodePipeline.
- Monitoring and Logging: CloudWatch, Azure Monitor, Stackdriver.
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Big Data and Machine Learning
- Data Processing: AWS EMR, Dataproc, Synapse.
- Machine Learning platforms: AWS SageMaker, Azure ML, GCP AI Platform.
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Hybrid and Multi-Cloud Strategies
- Kubernetes and Containers (EKS, AKS, GKE).
- Multi-cloud orchestration tools.
- Data migration between clouds.
Phase 5: Certifications (Optional but Recommended)
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AWS Certifications
- AWS Certified Solutions Architect – Associate.
- AWS Certified Developer – Associate.
- AWS Certified DevOps Engineer – Professional.
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Microsoft Azure Certifications
- Microsoft Certified: Azure Fundamentals (AZ-900).
- Microsoft Certified: Azure Administrator Associate (AZ-104).
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Google Cloud Certifications
- Google Associate Cloud Engineer.
- Google Professional Cloud Architect.
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Specialized Certifications
- CompTIA Cloud+.
- Certified Cloud Security Professional (CCSP).
Phase 6: Cloud Projects
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Basic Projects
- Deploy a static website on AWS S3.
- Set up a WordPress blog on EC2.
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Intermediate Projects
- Build a serverless application using AWS Lambda.
- Configure a multi-tier architecture with load balancers.
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Advanced Projects
- Implement CI/CD pipeline for a web application.
- Build a real-time chat application using serverless technologies.
- Create a data lake and analyze data using BigQuery or Redshift.
Phase 7: Emerging Trends in Cloud
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Edge Computing and IoT Integration
- AWS IoT Core, Azure IoT Hub, GCP IoT Core.
- Edge services and computing models.
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Sustainability in Cloud Computing
- Carbon-neutral cloud strategies.
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Quantum Computing on Cloud
- AWS Braket, Azure Quantum, Google Quantum AI.
Final Tips
- Regularly practice on cloud platforms to gain hands-on experience.
- Stay updated with new features and services released by cloud providers.
- Participate in cloud hackathons or open-source projects to apply your skills.
- Follow blogs, webinars, and tutorials by cloud experts.
Would you like a more detailed breakdown of any specific phase or assistance with creating a learning schedule?
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