What you would learn in DP-100: Azure Machine Learning & Data Science for Beginners course?
Machine Learning and Data Science are among the top fields in technology these days! There are plenty of opportunities within these areas. Data Science and Machine Learning are applied to nearly every area, such as banking, finance, transportation, Health, Defense, Entertainment, etc.
Most students and professionals learn Data Science and Machine Learning; however, they have particular issues when working in a cloud-based environment. To help solve this issue, I've designed a course called the DP-100 course, and it will allow you to utilize your data expertise in Azure Cloud smoothly.
This course will aid you in getting through your "Exam DP-100: Designing and Implementing a Data Science Solution on Azure". In this course, you'll know what to prepare for on the test and cover all subjects required for passing the DP-100 Exam.
Below are the competencies that will be tested in the DP-100 exam.
1.) Manage Azure resources for machine learning ( 25-30%)
Make the Azure Machine Learning workspace
Manage data in an Azure Machine Learning workspace
Control compute for experiments using Azure Machine Learning
Set up access and security within Azure Machine Learning
Create the Azure Machine Learning development environment
Create your Azure Databricks workspace
2) Test and run experiments, as well as model models to train (20-25 %)
Make models using Azure Machine Learning designer. Azure Machine Learning Designer
Run model training scripts
Make the metrics of an experiment that are derived from it.
Make use of automated Machine Learning to design optimal models
Adjust hyperparameters using Azure Machine Learning
3) Implement and deploy machine learning applications (35-40 percent)
Select compute for model deployment
Create a model to be deployed as a service
Manage models in Azure Machine Learning
Develop the Azure Machine Learning pipeline for batch inferencing
Release your Azure Machine Learning designer pipeline as an online service
Create pipelines using Azure Machine Learning SDK
Make use of ML Ops practices
4) Use responsible machine learning (5-10 percent)
Use model explanations to explain models
Discuss fairness considerations in models
Define privacy considerations for personal data
- Learn to pass the DP-100 exam.
- How to Get Started with Azure ML
- Setting up Azure Machine Learning Workspace
- Run Experiments, Training, and Models
- The Models are deployed
- AzureML Designer: Data Preprocessing
- Regression Using AzureML Designer
- Classification Using AzureML Designer
- AzureML SDK: Setting up Azure ML Workspace
- AzureML SDK for Running Experiments and Training Models
- Make use of automated ML to create optimal Models
- Adjust hyperparameters using Azure Machine Learning
- Use model explanations to explain models.
Download DP-100: Azure Machine Learning & Data Science for Beginners from below links NOW!