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DP-100T01: Designing and Implementing a Data Science Solution on Azure Training


What DP-100T01: Designing and Implementing a Data Science Solution on Azure training is all about?

DP-100T01: Designing and Implementing a Data Science Solution on Azure Training teaches the techniques to work with machine learning solutions at the cloud scale with the help of Azure Machine Learning. This technical course enhances and supports one’s current knowledge of machine learning and Python to manage data preparations and ingestions, model training, and launch machine learning solution inspection in Microsoft Azure. Our enterprise training program is best for organizations and companies. It teaches automation, management, and monitoring of machine learning using Azure Machine Learning service. This training program is ideal for data scientists with experience in machine learning frameworks and Python, who want to develop and work with machine learning solutions in the cloud. It is also very useful for individuals preparing for the Microsoft Certified: Azure Data Scientist Associate certification exam.

Schedule
  • Delivery Format:
Date: Nov 02, 2020 | 9:00 am - 5:00 pm EST
Location: Online
$1725 USD
  • Delivery Format:
Date: Dec 02, 2020 | 9:00 am - 5:00 pm EST
Location: Online
$1725 USD
What are the course objectives for DP-100T01: Designing and Implementing a Data Science Solution on Azure training?
  • Doing Data Science on Azure
  • Doing Data Science with Azure Machine Learning service
  • Automating Machine Learning with Azure Machine Learning service
  • Managing and Monitoring Machine Learning Models with the Azure Machine Learning service
Who should attend DP-100T01: Designing and Implementing a Data Science Solution on Azure training?

Data scientists who know Python and existing understanding of machine learning frameworks such as TensorFlow, PyTorch, and Scikit-Learn who want to create and manage machine learning solutions in the cloud are the primary audiences for this training.

What is the course outline for DP-100T01: Designing and Implementing a Data Science Solution on Azure training?
  • 1. Introduction to Azure Machine Learning
  • a). Getting Started with Azure Machine Learning
  • b). Azure Machine Learning Tools
  • c). Lab : Creating an Azure Machine Learning Workspace
  • d). Lab : Working with Azure Machine Learning Tools
  • 2. No-Code Machine Learning with Designer
  • a). Training Models with Designer
  • b). Publishing Models with Designer
  • c). Lab : Creating a Training Pipeline with the Azure ML Designer
  • d). Lab : Deploying a Service with the Azure ML Designer
  • 3. Running Experiments and Training Models
  • a). Introduction to Experiments
  • b). Training and Registering Models
  • c). Lab : Running Experiments
  • d). Lab : Training and Registering Models
  • 4. Working with Data
  • a). Working with Datastores
  • b). Working with Datasets
  • c). Lab : Working with Datastores
  • d). Lab : Working with Datasets
  • 5. Compute Contexts
  • a). Working with Environments
  • b). Working with Compute Targets
  • c). Lab : Working with Environments
  • d). Lab : Working with Compute Targets
  • 6. Orchestrating Operations with Pipelines
  • a). Introduction to Pipelines
  • b). Publishing and Running Pipelines
  • c). Lab : Creating a Pipeline
  • d). Lab : Publishing a Pipeline
  • 7. Deploying and Consuming Models
  • a). Real-time Inferencing
  • b). Batch Inferencing
  • c). Lab : Creating a Real-time Inferencing Service
  • d). Lab : Creating a Batch Inferencing Service
  • 8. Training Optimal Models
  • a). Hyperparameter Tuning
  • b). Automated Machine Learning
  • c). Lab : Tuning Hyperparameters
  • d). Lab : Using Automated Machine Learning
  • 9. Interpreting Models
  • a). Introduction to Model Interpretation
  • b). using Model Explainers
  • c). Lab : Reviewing Automated Machine Learning Explanations
  • d). Lab : Interpreting Models
  • 10. Monitoring Models
  • a). Monitoring Models with Application Insights
  • b). Monitoring Data Drift
  • c). Lab : Monitoring a Model with Application Insights
  • d). Lab : Monitoring Data Drift
3 Days | $ 1725
4.7
  279 Ratings

1478 Learners