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Cloud Computing Lvl2

Cloud Computing Lvl2

EGP4,000.00Price
This comprehensive course provides a deep dive into Google Cloud Platform (GCP), equipping students with the knowledge and skills to design, build, and manage scalable, secure, and cost-effective cloud solutions. Through hands-on labs and real-world case studies, students will master GCP's core services and advanced technologies, preparing them for professional roles in cloud architecture, development, and administration.

  • Course Outlines

    • Module 1: GCP Fundamentals (10 credit hours)

    • Introduction to Cloud Computing: Cloud concepts, service models (IaaS, PaaS, SaaS), deployment models, and the advantages of cloud computing.
    • GCP Overview: Global infrastructure, key services, pricing models, and account management.
    • Core Infrastructure: Compute Engine, Virtual Private Cloud (VPC), networking, storage options (Cloud Storage, persistent disks), and databases (Cloud SQL, Cloud Spanner).
    • Security and Identity: Identity and Access Management (IAM), security best practices, and compliance.

    • Module 2: Developing and Deploying Applications (15 credit hours)

    • App Engine: Deploying and scaling web applications and APIs.
    • Kubernetes Engine: Container orchestration, deploying and managing containerized applications.
    • Cloud Functions: Serverless computing, event-driven architecture, and building microservices.
    • Cloud Run: Deploying and scaling containerized applications on a serverless platform.
    • DevOps on GCP: Continuous integration and continuous delivery (CI/CD) pipelines, infrastructure as code (Terraform), and monitoring.

    • Module 3: Data Management and Analytics (15 credit hours)

    • BigQuery: Data warehousing, data analysis, and business intelligence.
    • Cloud Dataflow: Batch and stream data processing.
    • Cloud Dataproc: Managed Hadoop and Spark clusters for big data processing.
    • Cloud Pub/Sub: Real-time messaging and data ingestion.

    • Module 4: AI and Machine Learning (10 credit hours)

    • AI Platform: Building, training, and deploying machine learning models.
    • Vertex AI: Unified machine learning platform for building and deploying AI applications.
    • Pre-trained APIs: Leveraging Google's pre-trained models for vision, language, and structured data.
    • AutoML: Building custom machine learning models without coding.

    • Module 5: Advanced Cloud Architecture and Management (10 credit hours)

    • Cloud Networking: Advanced networking concepts, hybrid connectivity, and network security.
    • Cloud Monitoring and Logging: Observability, logging, and monitoring tools.
    • Cost Management: Optimizing cloud costs, budgeting, and billing analysis.
    • Reliability and Disaster Recovery: Designing for high availability, fault tolerance, and disaster recovery.
    • Google Cloud's Best Practices: Implementing best practices for security, performance, and cost optimization.

    • Assessment:

    • Hands-on Labs: Practical exercises on GCP to reinforce concepts and develop practical skills.
    • Quizzes: Regular assessments to test understanding of key topics.
    • Projects: Individual or group projects to design and implement cloud solutions.
    • Case Studies: Analyzing real-world scenarios and applying GCP services to solve business problems.
    • Final Exam: Comprehensive exam covering the entire course material.

  • hours:

    60 hr

  • Training Outcomes

    • Upon successful completion of this course, students will be able to:

    • Design and implement scalable and secure cloud solutions on GCP.
    • Deploy and manage applications using various GCP services.
    • Utilize GCP's data management and analytics tools to derive insights from data.
    • Leverage AI and machine learning services on GCP to build intelligent applications.
    • Optimize cloud costs and ensure high availability and disaster recovery.
    • Apply Google Cloud's best practices for security, performance, and cost optimization.

    • This course structure provides a comprehensive and in-depth learning experience, preparing students for a successful career in cloud computing with a specialization in Google Cloud Platform. The emphasis on hands-on labs, projects, and case studies ensures that graduates possess the practical skills and knowledge required to excel in real-world cloud environments.

    • Data Storage Options: Choosing the right storage solution for different data types and workloads.
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