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دسته بندی دوره ها

Data Science Model deployments and Cloud Computing on GCP

سرفصل های دوره

Learn to deploy and implement applications at scale using Kubelow, spark and serverless components on Google Cloud


1 - Course Introduction and prerequisites
  • 1 - Course Introduction and Section Walkthrough
  • 2 - Course Prerequisites
  • 3 - Course Material Github Repo.html

  • 2 - Modern Day Cloud Concepts
  • 4 - Introduction
  • 5 - Scalability Horizontal vs Vertical Scaling
  • 6 - Serverless Vs Servers and Containerization
  • 7 - Microservice Architecture
  • 8 - Event Driven Architecture

  • 3 - Get Started with Google Cloud
  • 9 - Setup GCP Trial Account
  • 10 - Gcloud CLI Setup
  • 11 - Get comfortable with basics of gcloud cli
  • 12 - gsutil and bash command basics

  • 4 - Cloud Run Serverless and containerized applications
  • 13 - Section Introduction
  • 14 - Introduction to Dockers
  • 15 - Lab Install Docker Engine
  • 16 - Lab Run Docker locally
  • 17 - Lab Run and ship applications using the container registry
  • 18 - Introduction to Cloud Run
  • 19 - LabDeploy python application to Cloud run
  • 20 - Cloud Run Application Scalability parameters
  • 21 - Introduction to Cloud Build
  • 22 - Lab Python application deployment using cloud build
  • 23 - LabContinuous Deployment using cloud build and github

  • 5 - Google App Engine For Serverless applications
  • 24 - Introduction to App Engine
  • 25 - App Engine Different Environments
  • 26 - LabDeploy Python application to App Engine Part 1
  • 27 - LabDeploy Python application to App Engine Part 2
  • 28 - LabTraffic splitting in App Engine
  • 29 - LabDeploy pythonbigquery application
  • 30 - What is Caching and the usecases
  • 31 - LabImplement Caching mechanism in python application Part 1
  • 32 - LabImplement Caching mechanism in python application Part 2
  • 33 - LabAssignment Implement Caching
  • 34 - LabPython App deployment in flexible environment
  • 35 - Lab Scalability and instance types in App Engine

  • 6 - Cloud Functions Serverless and event driven applications
  • 36 - Introduction
  • 37 - LabDeploy python application using cloud storage triggers
  • 38 - LabDeploy python application using pubsub triggers
  • 39 - LabDeploy python application using http triggers
  • 40 - Introduction to Cloud Datastore
  • 41 - Overview Product wishlist usecase
  • 42 - LabUsecase deployment part1
  • 43 - LabUsecase deployment part2

  • 7 - Data Science Models with Google App Engine
  • 44 - Introduction to ML Model Lifecycle
  • 45 - Overview Problem Statement
  • 46 - LabDeploy Training Code to App Engine
  • 47 - LabDeploy Model Serving Code to App Engine
  • 48 - OverviewNew Use Case
  • 49 - LabData Validation using App Engine
  • 50 - LabWorkflow Template introduction
  • 51 - LabFinal Solution Deployment using workflow and app engine

  • 8 - Dataproc Serverless Pyspark
  • 52 - Introduction
  • 53 - PySpark Serverless Autoscaling Properties
  • 54 - Persistent History Cluster
  • 55 - Lab Develop and Submit Pyspark Job
  • 56 - LabMonitoring and Spark UI
  • 57 - Introduction to Airflow
  • 58 - Lab Airflow with Serverless pyspark
  • 59 - Wrap Up

  • 9 - Vertex AI Machine Learning Framework
  • 60 - Introduction
  • 61 - Overview VertexAI UI
  • 62 - LabCustom Model training using Web Console
  • 63 - LabCustom Model training using SDK and Model Registries
  • 64 - Lab Model Endpoint Deployment
  • 65 - Lab Model Training Flow using Python SDK
  • 66 - Lab Model Deployment Flow using Python SDK
  • 67 - LabModel Serving using Endpoint with Python SDK
  • 68 - Introduction to Kubeflow
  • 69 - LabCode Walkthrough using Kubeflow and Python
  • 70 - LabPipeline Execution in Kubeflow
  • 71 - LabFinal Pipeline Visualization using Vertex UI and Walkthrough
  • 72 - LabAdd Model Evaluation Step in Kubeflow before deployment
  • 73 - Lab Reusing configuration files for pipeline execution and training
  • 74 - Lab Assignment Usecase Fetch data from BigQuery
  • 75 - Wrap Up

  • 10 - Cloud Scheduler and Application Monitoring
  • 76 - Introduction to Cloud Scheduler
  • 77 - LabCloud Scheduler in action
  • 78 - Lab Setup Alerting for Google App Engine Applications
  • 79 - Lab Setup Alerting for Cloud Run Applications
  • 80 - Lab Assignment Setup Alerting for Cloud Function Applications
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