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Terminy kursów:

29.06.2020 - 01.07.2020

Oficjalny konspekt Microsoft Pozostałe szkolenia

DP-100 Designing and Implementing a Data Science Solution on Azure

Czas trwania kursu: 3 dni
Cena: 1999 zł netto

CERTYFIKACJE ZAWODOWE

Certyfikacja podstawowa CertyfIkacja specjalistyczna Certyfikacja ekspercka
FUNDAMENTALS ASSOCIATE EXPERT

 


POZIOM SZKOLENIA

podstawowy średniozaawansowany zaawansowany ekspercki
100 200 300 400

 

TEMATYKA ZAJĘĆ

  • Module 1: Introduction to Azure Machine Learning
    Getting Started with Azure Machine Learning
    Azure Machine Learning Tools
    Lab : Creating an Azure Machine Learning Workspace
    Lab : Working with Azure Machine Learning Tools

 

  • Module 2: No-Code Machine Learning with Designer
    Training Models with Designer
    Publishing Models with Designer
    Lab : Creating a Training Pipeline with the Azure ML Designer
    Lab : Deploying a Service with the Azure ML Designer

 

  • Module 3: Running Experiments and Training Models
    Introduction to Experiments
    Training and Registering Models
    Lab : Running Experiments
    Lab : Training and Registering Models

 

  • Module 4: Working with Data
    Working with Datastores
    Working with Datasets
    Lab : Working with Datastores
    Lab : Working with Datasets

 

  • Module 5: Compute Contexts
    Working with Environments
    Working with Compute Targets
    Lab : Working with Environments
    Lab : Working with Compute Targets

 

  • Module 6: Orchestrating Operations with Pipelines
    Introduction to Pipelines
    Publishing and Running Pipelines
    Lab :
    Creating a Pipeline
    Lab :
    Publishing a Pipeline

 

  • Module 7: Deploying and Consuming Models
    Real-time Inferencing
    Batch Inferencing
    Lab : Creating a Real-time Inferencing Service
    Lab : Creating a Batch Inferencing Service

 

  • Module 8: Training Optimal Models
    Hyperparameter Tuning
    Automated Machine Learning
    Lab : Tuning Hyperparameters
    Lab : Using Automated Machine Learning

 

  • Module 9: Interpreting Models
    Introduction to Model Interpretation
    using Model Explainers
    Lab : Reviewing Automated Machine Learning Explanations
    Lab : Interpreting Models

 

  • Module 10: Monitoring Models
    Monitoring Models with Application Insights
    Monitoring Data Drift
    Lab : Monitoring a Model with Application Insights
    Lab : Monitoring Data Drift