A Brief About Microsoft Certified: Azure Data Scientist – Associate Exam DP-100
IT professionals, willing to develop their career in the field of Data Science and need recognition, may find Microsoft Certified: Azure Data Scientist – Associate Exam DP-100 as their best option to start with. This certification validates the capability of an IT professional to work with the tools and applications used in Data Science and/or relevant fields under the Azure platform. This certification also allows the IT professionals to work mostly as an Azure Data Scientist who is able to deploy machine learning workloads on Azure platform. This includes both the designing and deploying an effective and flawless working environment to execute data experiments; train, manage and optimize machine learning models.
Course curriculum of DP – 100 exam was updated last on 22nd May, 2020. As one of the vendor specific
Skills Measured of DP – 100 Exam
Microsoft has distributed the content of DP – 100 exam in four different segments. Total weight of the exam is not equally distributed. Followings are the skills measured in DP – 100 exam:
· Deploy the Workspace for Azure Machine Learning
(Weight: 30% to 35%)
I. Design and Develop a Workspace for Azure Machine Learning
a. Configure and troubleshoot the settings of the Workspace.
b. Control the Workspace using Azure Machine Learning Studio.
II. Control data objects in Azure Machine Learning Workspace.
a. Maintain the documentation process for stored data.
b. Develop and configure the dataset.
III. Control experiment computes contexts
a. Develop a compute instance.
b. Measure appropriate compute specifications to train a workload.
c. Develop compute targets for testing and training.
· Execute experiments and train the models
(Weight: 25% to 30%)
I. Develop Models using Azure Machine Learning Designer
a. Develop a training pipeline by using Azure Machine Learning Designer.
b. Retrieve and restore data in a pipeline.
c. Utilize designer modules to define a pipeline data flow.
d. Implement customized code modules in designer.
II. Execute and test model training scripts in Azure Machine Learning Workspace
a. Develop and run an experiment by using the Azure Machine Learning SDK.
b. Restore data from a data source in a trial run by using the Azure Machine Learning SDK.
c. Restore data from a dataset in an experiment by using the Azure Machine Learning SDK.
d. Select an estimator for a trial run.
III. Create matrics from an experimental execution.
a. Maintain the log metrics from a trial run.
b. Extract and observe the outputs from an experiment.
c. Utilize the logs to troubleshoot the errors from the experiment.
IV. Automate the model training process.
a. Develop a pipeline using the Azure Machine Learning SDK.
b. Ensure the transaction of data between steps in a pipeline.
c. Install and execute a pipeline.
d. Observe the result from a pipeline run.
· Enhance and Manage Machine Learning Model.
(Weight: 20% to 25%)
I. Implement automated Machine Learning to develop optimal models
a. Implement the automated Machine Learning Interface in Azure Machine Learning Studio.
b. Use automated Machine Learning from the Azure Machine Learning SDK.
c. Choose scaling functions and available options for pre-processing.
d. Select an appropriate search algorithm.
e. Select a primary metric.
f. Retrieve data for an automated Machine Learning run.
g. Prefer the best model for Azure Machine Learning platform.
II. Use Hyperdrive to configure Hyperparameters
a. Choose a sampling method.
b. Determine the search space.
c. Determine the primary metric.
d. Determine the best option for early termination.
e. Select the best model to get hyperparameter values.
III. Utilize Model Explainers to understand the Models
a. Choose an appropriate model interpreter.
b. Create feature importance data.
IV. Control Models
a. Register a trained model.
b. Investigate model history.
c. Monitor data drift.
· Install and Configure the Machine Learning Model.
(Weight: 20% to 25%)
I. Develop production compute targets
a. Ensure the security for the installed services.
b. Estimates compute option for installation.
II. Install a model as a service
a. Configure the installation settings.
b. Consume an installed service.
c. Troubleshoot deployment container issues.
III. Develop a pipeline for batch inferencing
a. Produce a batch inferencing pipeline.
b. Execute a batch inferencing pipeline and get the outputs.
IV. Develop and deploy a pipeline as a web service
a. Develop a target compute resource.
b. Configure an inference pipeline.
c. Consume a deployed endpoint.
Details About the Exam
· Name of the Certification Exam: Designing and Implementing a Data Science Solution on Azure.
· Exam Code: DP – 100.
· Duration of the Exam: Three hours.
· Total marks: 1000.
· Passing score: 700.
· Total number of questions: 40 to 60.
· Format of the question: Fill in the banks, multiple choice and case studies.
· Cost of exam: £129.
Average salary of DP – 100 certified professionals
DP – 100 Certified Professionals are getting paid between £89,588 to £112,960.
Job Roles of DP – 100 Certified Professionals:
Usually, DP – 100 certified professionals are working as:
· Machine Learning Engineer.
· Information Security Analyst.
· Mainframe Developer.
· Senior System Support Analyst.
· Infrastructure Solution Architect.
Prerequisites For DP – 100
The vendor (Microsoft) specific certification exam, Designing and Implementing a Data Science Solution on Azure (DP – 100) has no particular prerequisite, though it is recommended that the candidates for this exam are familiar with the basic principles of Data Science Workflows and Microsoft Azure platform.
Getting Prepared For The Exam
We are offering both the instructor-led and self-paced online courses to make you well prepared for the certification, Designing and Implementing a Data Science Solution on Azure. We have plenty of resources, which you can access from anywhere through the internet. We are also offering practice tests, through which you will be used to know more about the pattern and the types of questions of DP – 100 certified exam. Our training program is not designed only to get well prepared for the exam and earn the certificate successfully, but we have skilled and professional individuals who will help you to get a professionally designed CV to catch your dream job. Our job placement program is another reason for you to choose us, as we are working closely in collaboration with IT companies across the UK.