Duration: Hours

Training Mode: Online

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    Description

    A cloud ML platform provides the compute, storage, and services required to train machine learning models. Cloud computing makes machine learning more accessible, flexible, and cost-effective while allowing developers to build ML algorithms faster.

    Course Content

    1- Comprehensive Cloud Computing Course (C4)

    • About Cloud Technology
    • Introduction to AWS, GCP, AZURE

    2-AWS

    • AWS Cloud Architecture & Infrastructure Details
    • AWS Elastic Compute Cloud Services (EC2) – EC2
    • Amazon Web Services Networking & Content Delivery Services
    • AWS Simple Storage Services (S3)
    • AWS Relational Database Service (RDS)
    • Database Services
    • IAM & Monitoring Services
    • AWS Monitoring & Notification Services
    • Decision Tree and Random Forest Models

    3-GCP

    • Setting Up A Cloud Solution Environment
    • Planning And Configuring A Cloud Solution
    • Deploying And Implementing A Cloud Solution
    • Ensuring Successful Operation Of A Google Cloud Solution
    • Configuring Access And Security In GCP
    • Decision Tree And Random Forest Models

    4-Azure

    • Deploying and Configuring Your Infrastructure
    • Implementation of Azure Security and Workloads
    • Broad Understanding of Azure Cloud Architecting Technology And Solutions
    • How to Create Apps and Deploying Them
    • Ways of Developing For the Azure Cloud
    • Designing for Azure Identity and Security
    • Azure Data Platform Solution Designing
    • How to Deploy Migrate and Integrate With Azure Cloud
    • Infrastructure Strategy
    • Decision Tree and Random Forest Models

     5-Machine Learning

    • Machine Learning
    • AWS – Machine Learning
    • Microsoft Azure – Machine Learning Studio
    • GCP – Google Cloud Machine Learning (ML) Engine

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