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

Vendor : Microsoft
Exam Code : DP-100
Exam Name : Designing and Implementing a Data Science Solution on Azure
Questions and Answers : 215 Q & A
Updated On : Click to Check Update
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DP-100 Questions and Answers

DP-100.html


Question #4 Section 9 Introductory Info Case study -

Overview -

You are a data scientist in a company that provides data science for professional sporting events. Models will use global and local market data to meet the following business goals: Understand sentiment of mobile device users at sporting events based on audio from crowd reactions.

Assess a userג€™s tendency to respond to an advertisement. Customize styles of ads served on mobile devices.

Use video to detect penalty events


Current environment -

Media used for penalty event detection will be provided by consumer devices. Media may include images and videos captured during the sporting event and shared using social media. The images and videos will have varying sizes and formats.

The data available for model building comprises of seven years of sporting event media. The sporting event media includes; recorded video transcripts or radio commentary, and logs from related social media feeds captured during the sporting events.

Crowd sentiment will include audio recordings submitted by event attendees in both mono and stereo formats.


Penalty detection and sentiment -

Data scientists must build an intelligent solution by using multiple machine learning models for penalty event detection.

Data scientists must build notebooks in a local environment using automatic feature engineering and model building in machine learning pipelines. Notebooks must be deployed to retrain by using Spark instances with dynamic worker allocation.

Notebooks must execute with the same code on new Spark instances to recode only the source of the data. Global penalty detection models must be trained by using dynamic runtime graph computation during training. Local penalty detection models must be written by using BrainScript.

Experiments for local crowd sentiment models must combine local penalty detection data.

Crowd sentiment models must identify known sounds such as cheers and known catch phrases. Individual crowd sentiment models will detect similar sounds. All shared features for local models are continuous variables.

Shared features must use double precision. Subsequent layers must have aggregate running mean and standard deviation metrics available.


Advertisements -

During the initial weeks in production, the following was observed: Ad response rated declined.

image

Drops were not consistent across ad styles.

The distribution of features across training and production data are not consistent

Analysis shows that, of the 100 numeric features on user location and behavior, the 47 features that come from location sources are being used as raw features. A suggested experiment to remedy the bias and variance issue is to engineer 10 linearly uncorrelated features.

Initial data discovery shows a wide range of densities of target states in training data used for crowd sentiment models. All penalty detection models show inference phases using a Stochastic Gradient Descent (SGD) are running too slow. Audio samples show that the length of a catch phrase varies between 25%-47% depending on region

The performance of the global penalty detection models shows lower variance but higher bias when comparing training and validation sets. Before implementing any feature changes, you must confirm the bias and variance using all training and validation cases.

Ad response models must be trained at the beginning of each event and applied during the sporting event. Market segmentation models must optimize for similar ad response history.

Sampling must guarantee mutual and collective exclusively between local and global segmentation models that share the same features. Local market segmentation models will be applied before determining a userג€™s propensity to respond to an advertisement.

Ad response models must support non-linear boundaries of features.

The ad propensity model uses a cut threshold is 0.45 and retrains occur if weighted Kappa deviated from 0.1 +/- 5%. The ad propensity model uses cost factors shown in the following diagram:

image

The ad propensity model uses proposed cost factors shown in the following diagram:

image

Performance curves of current and proposed cost factor scenarios are shown in the following diagram:



image

response models as illustrated in the performance curve exhibit. Which technique should you use?

Question You need to implement a new cost factor scenario for the ad


image

  1. Set the threshold to 0.5 and retrain if weighted Kappa deviates +/- 5% from 0.45.

    image

  2. Set the threshold to 0.05 and retrain if weighted Kappa deviates +/- 5% from 0.5.

    image

  3. Set the threshold to 0.2 and retrain if weighted Kappa deviates +/- 5% from 0.6.

    image

  4. Set the threshold to 0.75 and retrain if weighted Kappa deviates +/- 5% from 0.15.


Answer: A Scenario:

Performance curves of current and proposed cost factor scenarios are shown in the following diagram:

image

The ad propensity model uses a cut threshold is 0.45 and retrains occur if weighted Kappa deviated from 0.1 +/- 5%. Develop models

Question #1 Section 10 Introductory Info Case study -

This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies

and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.

To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.

At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.


To start the case study -

To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an

All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.

Overview -

You are a data scientist for Fabrikam Residences, a company specializing in quality private and commercial property in the United States. Fabrikam Residences is considering expanding into Europe and has asked you to investigate prices for private residences in major European cities.

You use Azure Machine Learning Studio to measure the median value of properties. You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules.


Datasets -

There are two datasets in CSV format that contain property details for two cities, London and Paris. You add both files to Azure Machine Learning Studio as separate datasets to the starting point for an experiment. Both datasets contain the following columns:

image

An initial investigation shows that the datasets are identical in structure apart from the MedianValue column. The smaller Paris dataset contains the MedianValue in text format, whereas the larger London dataset contains the MedianValue in numerical format.

Data issues - Missing values -

The AccessibilityToHighway column in both datasets contains missing values. The missing data must be replaced with new data so that it is modeled conditionally using the other

variables in the data before filling in the missing values.

Columns in each dataset contain missing and null values. The datasets also contain many outliers. The Age column has a high proportion of outliers. You need to remove the rows that have outliers in the Age column. The MedianValue and AvgRoomsInHouse columns both hold data in numeric format. You need to select a feature selection algorithm to analyze the relationship between the two columns in more detail.


Model fit -

The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting.


Experiment requirements -

You must set up the experiment to cross-validate the Linear Regression and Bayesian Linear Regression modules to evaluate performance. In each case, the predictor of the dataset is the column named MedianValue. You must ensure that the datatype of the MedianValue column of the Paris dataset matches the structure of the London dataset.

You must prioritize the columns of data for predicting the outcome. You must use non-parametric statistics to measure relationships. You must use a feature selection algorithm to analyze the relationship between the MedianValue and AvgRoomsInHouse columns.


Model training -


Permutation Feature Importance -

Given a trained model and a test dataset, you must compute the Permutation Feature Importance scores of feature variables. You must be determined the absolute fit for the model.


Hyperparameters -

You must configure hyperparameters in the model learning process to speed the learning phase. In addition, this configuration should cancel the lowest performing runs at each evaluation interval, thereby directing effort and resources towards models that are more likely to be successful.

You are concerned that the model might not efficiently use compute resources in hyperparameter tuning. You also are concerned that the model might prevent an increase in the overall tuning time. Therefore, must implement an early stopping criterion on models that provides savings without terminating promising jobs.

Testing -

You must produce multiple partitions of a dataset based on sampling using the Partition and Sample module in Azure Machine Learning Studio.


Cross-validation -

You must create three equal partitions for cross-validation. You must also configure the cross-validation process so that the rows in the test and training datasets are divided evenly by properties that are near each cityג€™s main river. You must complete this task before the data goes through the sampling process.


Linear regression module -

When you train a Linear Regression module, you must determine the best features to use in a model. You can choose standard metrics provided to measure performance before and after the feature importance process completes. The distribution of features across multiple training models must be consistent.


Data visualization -

You need to provide the test results to the Fabrikam Residences team. You create data visualizations to aid in presenting the results.

You must produce a Receiver Operating Characteristic (ROC) curve to conduct a diagnostic test evaluation of the model. You need to select appropriate methods for producing the ROC curve in Azure Machine Learning Studio to compare the Two-Class Decision Forest and the Two-Class Decision Jungle modules with one another. Question DRAG DROP - You need to implement an early stopping criteria policy for model training.

Which three code segments should you use to develop the solution? To answer, move the appropriate code segments from the list of code segments to the answer area and arrange them in the correct order.

NOTE: More than one order of answer choices is correct. You will receive credit for any of the correct orders you select. Select and Place:

image


image

Answer:

You need to implement an early stopping criterion on models that provides savings without terminating promising jobs.

Truncation selection cancels a given percentage of lowest performing runs at each evaluation interval. Runs are compared based on their performance on the primary metric and the lowest X% are terminated.

Example:

from azureml.train.hyperdrive import TruncationSelectionPolicy early_termination_policy = TruncationSelectionPolicy(evaluation_interval=1, truncation_percentage=20, delay_evaluation=5)

Incorrect Answers:

Bandit is a termination policy based on slack factor/slack amount and evaluation interval. The policy early terminates any runs where the primary metric is not within the specified slack factor / slack amount with respect to the best performing training run.

Example:

from azureml.train.hyperdrive import BanditPolicy

early_termination_policy = BanditPolicy(slack_factor = 0.1, evaluation_interval=1, delay_evaluation=5 Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-tune-hyperparameters

Question #2 Section 10 Introductory Info Case study -

This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.

To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.

At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.


To start the case study -

To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an

All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.


Overview -

You are a data scientist for Fabrikam Residences, a company specializing in quality private and commercial property in the United States. Fabrikam Residences is considering

expanding into Europe and has asked you to investigate prices for private residences in major European cities.

You use Azure Machine Learning Studio to measure the median value of properties. You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules.


Datasets -

There are two datasets in CSV format that contain property details for two cities, London and Paris. You add both files to Azure Machine Learning Studio as separate datasets to the starting point for an experiment. Both datasets contain the following columns:

image

An initial investigation shows that the datasets are identical in structure apart from the MedianValue column. The smaller Paris dataset contains the MedianValue in text format, whereas the larger London dataset contains the MedianValue in numerical format.

Data issues - Missing values -

The AccessibilityToHighway column in both datasets contains missing values. The missing data must be replaced with new data so that it is modeled conditionally using the other

variables in the data before filling in the missing values.

Columns in each dataset contain missing and null values. The datasets also contain many outliers. The Age column has a high proportion of outliers. You need to remove the rows that have outliers in the Age column. The MedianValue and AvgRoomsInHouse columns both hold data in numeric format. You need to select a feature selection algorithm to analyze the relationship between the two columns in more detail.


Model fit -

The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting.


Experiment requirements -

You must set up the experiment to cross-validate the Linear Regression and Bayesian Linear Regression modules to evaluate performance. In each case, the predictor of the dataset is the column named MedianValue. You must ensure that the datatype of the MedianValue column of the Paris dataset matches the structure of the London dataset.

You must prioritize the columns of data for predicting the outcome. You must use non-parametric statistics to measure relationships. You must use a feature selection algorithm to analyze the relationship between the MedianValue and AvgRoomsInHouse columns.


Model training -


Permutation Feature Importance -

Given a trained model and a test dataset, you must compute the Permutation Feature Importance scores of feature variables. You must be determined the absolute fit for the model.


Hyperparameters -

You must configure hyperparameters in the model learning process to speed the learning phase. In addition, this configuration should cancel the lowest performing runs at each evaluation interval, thereby directing effort and resources towards models that are more likely to be successful.

You are concerned that the model might not efficiently use compute resources in hyperparameter tuning. You also are concerned that the model might prevent an increase in the overall tuning time. Therefore, must implement an early stopping criterion on models that provides savings without terminating promising jobs.


Testing -

You must produce multiple partitions of a dataset based on sampling using the Partition and Sample module in Azure Machine Learning Studio.


Cross-validation -

You must create three equal partitions for cross-validation. You must also configure the cross-validation process so that the rows in the test and training datasets are divided evenly by properties that are near each cityג€™s main river. You must complete this task before the data goes through the sampling process.


Linear regression module -

When you train a Linear Regression module, you must determine the best features to use in a model. You can choose standard metrics provided to measure performance before and after the feature importance process completes. The distribution of features across multiple training models must be consistent.


Data visualization -

You need to provide the test results to the Fabrikam Residences team. You create data visualizations to aid in presenting the results.

You must produce a Receiver Operating Characteristic (ROC) curve to conduct a diagnostic test evaluation of the model. You need to select appropriate methods for producing the ROC curve in Azure Machine Learning Studio to compare the Two-Class Decision Forest and the Two-Class Decision Jungle modules with one another. Question DRAG DROP - You need to correct the model fit issue.

Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order. Select and Place:

image


image

Answer:

Step 1: Augment the data -

Scenario: Columns in each dataset contain missing and null values. The datasets also contain many outliers. Step 2: Add the Bayesian Linear Regression module.

Scenario: You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules. Step 3: Configure the regularization weight.

Regularization typically is used to avoid overfitting. For example, in L2 regularization weight, type the value to use as the weight for L2 regularization. We recommend that you use a non-zero value to avoid overfitting.

Scenario:

Model fit: The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting. Incorrect Answers:

Multiclass Decision Jungle module:

Decision jungles are a recent extension to decision forests. A decision jungle consists of an ensemble of decision directed acyclic graphs (DAGs). L-BFGS:

L-BFGS stands for "limited memory Broyden-Fletcher-Goldfarb-Shanno". It can be found in the wwo-Class Logistic Regression module, which is used to create a logistic regression model that can be used to predict two (and only two) outcomes.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regr ession

Question #3 Section 10 Introductory Info Case study -

This is a case study. Case studies are not timed separately. You can use as much exam time as you would like to complete each case. However, there may be additional case studies and sections on this exam. You must manage your time to ensure that you are able to complete all questions included on this exam in the time provided.

To answer the questions included in a case study, you will need to reference information that is provided in the case study. Case studies might contain exhibits and other resources that provide more information about the scenario that is described in the case study. Each question is independent of the other questions in this case study.

At the end of this case study, a review screen will appear. This screen allows you to review your answers and to make changes before you move to the next section of the exam. After you begin a new section, you cannot return to this section.

To start the case study -

To display the first question in this case study, click the Next button. Use the buttons in the left pane to explore the content of the case study before you answer the questions. Clicking these buttons displays information such as business requirements, existing environment, and problem statements. If the case study has an

All Information tab, note that the information displayed is identical to the information displayed on the subsequent tabs. When you are ready to answer a question, click the Question button to return to the question.


Overview -

You are a data scientist for Fabrikam Residences, a company specializing in quality private and commercial property in the United States. Fabrikam Residences is considering expanding into Europe and has asked you to investigate prices for private residences in major European cities.

You use Azure Machine Learning Studio to measure the median value of properties. You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules.


Datasets -

There are two datasets in CSV format that contain property details for two cities, London and Paris. You add both files to Azure Machine Learning Studio as separate datasets to the starting point for an experiment. Both datasets contain the following columns:

image

An initial investigation shows that the datasets are identical in structure apart from the MedianValue column. The smaller Paris dataset contains the MedianValue in text format, whereas the larger London dataset contains the MedianValue in numerical format.

Data issues - Missing values -

The AccessibilityToHighway column in both datasets contains missing values. The missing data must be replaced with new data so that it is modeled conditionally using the other

variables in the data before filling in the missing values.

Columns in each dataset contain missing and null values. The datasets also contain many outliers. The Age column has a high proportion of outliers. You need to remove the rows that have outliers in the Age column. The MedianValue and AvgRoomsInHouse columns both hold data in numeric format. You need to select a feature selection algorithm to analyze the relationship between the two columns in more detail.


Model fit -

The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting.


Experiment requirements -

You must set up the experiment to cross-validate the Linear Regression and Bayesian Linear Regression modules to evaluate performance. In each case, the predictor of the dataset is the column named MedianValue. You must ensure that the datatype of the MedianValue column of the Paris dataset matches the structure of the London dataset.

You must prioritize the columns of data for predicting the outcome. You must use non-parametric statistics to measure relationships. You must use a feature selection algorithm to analyze the relationship between the MedianValue and AvgRoomsInHouse columns.


Model training -


Permutation Feature Importance -

Given a trained model and a test dataset, you must compute the Permutation Feature Importance scores of feature variables. You must be determined the absolute fit for the model.


Hyperparameters -

You must configure hyperparameters in the model learning process to speed the learning phase. In addition, this configuration should cancel the lowest performing runs at each evaluation interval, thereby directing effort and resources towards models that are more likely to be successful.

You are concerned that the model might not efficiently use compute resources in hyperparameter tuning. You also are concerned that the model might prevent an increase in the overall tuning time. Therefore, must implement an early stopping criterion on models that provides savings without terminating promising jobs.


Testing -

You must produce multiple partitions of a dataset based on sampling using the Partition and Sample module in Azure Machine Learning Studio.


Cross-validation -

You must create three equal partitions for cross-validation. You must also configure the cross-validation process so that the rows in the test and training datasets are divided evenly by properties that are near each cityג€™s main river. You must complete this task before the data goes through the sampling process.


Linear regression module -

When you train a Linear Regression module, you must determine the best features to use in a model. You can choose standard metrics provided to measure performance before and after the feature importance process completes. The distribution of features across multiple training models must be consistent.


Data visualization -

You need to provide the test results to the Fabrikam Residences team. You create data visualizations to aid in presenting the results.

You must produce a Receiver Operating Characteristic (ROC) curve to conduct a diagnostic test evaluation of the model. You need to select appropriate methods for producing the ROC curve in Azure Machine Learning Studio to compare the Two-Class Decision Forest and the Two-Class Decision Jungle modules with one another. Question DRAG DROP - You need to implement early stopping criteria as stated in the model training requirements.

Which three code segments should you use to develop the solution? To answer, move the appropriate code segments from the list of code segments to the answer area and arrange them in the correct order.

NOTE: More than one order of answer choices is correct. You will receive the credit for any of the correct orders you select. Select and Place:

image


image

Answer:

Step 1: from azureml.train.hyperdrive Step 2: Import TruncationCelectionPolicy

Truncation selection cancels a given percentage of lowest performing runs at each evaluation interval. Runs are compared based on their performance on the primary metric and the lowest X% are terminated.

Scenario: You must configure hyperparameters in the model learning process to speed the learning phase. In addition, this configuration should cancel the lowest performing runs at each evaluation interval, thereby directing effort and resources towards models that are more likely to be successful.

Step 3: early_terminiation_policy = TruncationSelectionPolicy.. Example:

from azureml.train.hyperdrive import TruncationSelectionPolicy early_termination_policy = TruncationSelectionPolicy(evaluation_interval=1, truncation_percentage=20, delay_evaluation=5)

In this example, the early termination policy is applied at every interval starting at evaluation interval 5. A run will be terminated at interval 5 if its performance at interval 5 is in the lowest 20% of performance of all runs at interval 5.

Incorrect Answers: Median:

Median stopping is an early termination policy based on running averages of primary metrics reported by the runs. This policy computes running averages across all training runs and terminates runs whose performance is worse than the median of the running averages.

Slack:

Bandit is a termination policy based on slack factor/slack amount and evaluation interval. The policy early terminates any runs where the primary metric is not within the specified slack factor / slack amount with respect to the best performing training run.

Reference:

https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-tune-hyperparameters Develop models


Microsoft DP-100 Exam (Designing and Implementing a Data Science Solution on Azure) Detailed Information

Microsoft Certification Program benefits
Learn about the benefits of the Microsoft Certification Program. Find answers to frequently asked questions regarding program benefits and Microsoft accounts.
Program benefits
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Q. What are the benefits of achieving a Microsoft Certification?
Microsoft Certification is an industry standard that is recognised worldwide. After you earn your Microsoft Certification, you have access to a number of benefits, which can be found on your benefits and exams dashboard.
Q. What will I find on the benefits and exams dashboard and who has access?
Individuals who have passed a Microsoft exam have access to the benefits and exams dashboard.
On the site, you will find:
A downloadable version of your certificate (you can order a printed copy); MOS members will need their Certiport login information
Your official Microsoft Certification downloadable transcript and access to the transcript-sharing tool
A tool to create and download certification logos
Your contact preferences and profile
Your Certification Planner
A sign up for the MCP Flash newsletters
Promotional offers, discounts and additional services
Q. What is a Charter certificate?
Charter Members are the pioneering group of individuals who achieve a certification within six months following the retail release date of the certification. (People who pass the beta exams will receive the Charter certificate after the certification is commercially released.) Charter Members are recognised by being given the Charter version of the certificate acknowledging their early adoption of the technology solution. The Charter version of the certificate includes the word "Charter".
Q. Which certifications are eligible for Charter status?
If you have any of the following certifications, you are eligible for the Charter certificate: Microsoft Certified Solutions Associate (MCSA), Microsoft Certified Solutions Expert (MCSE), Microsoft Certified Solutions Developer (MCSD), Microsoft Certified Technology Specialist (MCTS), Microsoft Certified IT Professional (MCITP), Microsoft Certified Solutions Master (MCSM), or Microsoft Certified Professional Developer (MCPD). Exceptions include those certifications that are released when the technology covered is no longer the latest version of the technology. These include the MCSA: Windows 7, the MCSA: SQL Server 2008 and the MCSA: Windows Server 2008.
In addition, Microsoft Specialist (Specialist) certifications released in and after September 2015 are also eligible for Charter status, including all Windows 10, Big Data Analytics and Cloud Data Platform Specialist certifications.
Q. How much time do I have to order my Charter certificate?
You can digitally download or order your Charter certificate at any point after it is earned.
Q. When does the Charter certificate period start for localised exams?
The six-month "clock" start time is based on the earliest time the certification can be earned, which is typically based on English-language exam availability. For example, if an exam is available in German two months after the English version is available, the German candidate has only four more months to earn a Charter certificate.
Q. I have heard that Microsoft sponsors an Elevate America veterans initiative to help our country's veterans and their spouses acquire the skills and resources that they need to be successful in today's workplace. What is this initiative?
Through this initiative, Microsoft convenes a coalition of public, private and non-profit organisations that are interested in contributing expertise, cash and in-kind resources to help U.S. veterans and their spouses build the skills and access the resources that they need to be successful in today's workforce.
Accessing the benefits and exams dashboard
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Q. How do I qualify for access to the benefits and exams dashboard?
The benefits and exams dashboard is available if you have passed a Microsoft qualified exam. It provides customised resources specific to your achievements and certifications.
Sign in to the benefits and exams dashboard
Q. How do I access the Microsoft Certification benefits and exams dashboard for the first time?
After you pass your first Microsoft Certification exam, you will receive a welcome email message outlining the steps needed to gain access to the benefits and exams dashboard. Please check your junk folder to ensure that the automatic email message is not blocked by your spam filter. Here are the instructions you will receive in the email message.
Create a Microsoft account if you don't already have one.
On your first visit, click on the link provided in the email and use your Microsoft account to log in to the benefits and exams dashboard.
Note This must be done within 90 days of receiving the email to meet security requirements.
In some cases, you may be required to enter your Microsoft Certification ID (MC ID) and temporary access code, which will be supplied in the email message.
On future visits, log in to the benefits and exams dashboard using the same Microsoft account.
For assistance, go to Microsoft training and certification help.
Q. I do not know my Microsoft Certification ID (formerly MCP ID). What should I do?
Your MC ID is shown in your welcome email as well as in the profile information on the benefits and exams dashboard. If you are unable to access the benefits and exams dashboard, contact your Microsoft Regional Service Centre for assistance.
Q. What is the access code required for the benefits and exams dashboard?
An access code is a unique code that allows first-time access to the benefits and exams dashboard and, if required, is provided in your welcome email. You can only use the access code to sign in to the benefits and exams dashboard for the first time. If you misplace your code or it has retired, contact your Microsoft Regional Service Centre for assistance.
Q. How long does it take for my data to update after accessing the benefits and exams dashboard for the first time?
After you register, you must wait 24 hours before accessing your program benefits.
Q. I am a returning user and cannot access the benefits and exams dashboard. How do I gain access?
If you cannot remember the Microsoft account information associated with your account, or you have other difficulty accessing the benefits and exams dashboard, contact the Microsoft Regional Service Centre in your area.
Note If you have a Hotmail account, MSN email account or Microsoft Passport, it is your Microsoft account.
Q. I saved the URL to my Microsoft Certification Program benefits in my Favourites, but when I navigate there I am redirected to a sign-in page, not the page I am trying to access.
Because online benefits are available only to eligible Microsoft Certification Program members, you must enter your Microsoft account credentials to access your online benefits. After your account is authenticated, you will be redirected to the page you are trying to access.
Q. Why is my name on the benefits and exams dashboard different from what it is in my Microsoft Personal Profile?
You are required to use your legal name for the benefits and exams dashboard. The Microsoft Personal Profile is associated with your Microsoft account.
Q. How do I update my legal name?
To update your legal name, contact your Microsoft Regional Service Centre.
Q. How do I update the information in my Microsoft Personal Profile?
You can update your Microsoft Personal Profile in the Profile Centre.
To change the name that is associated with your Microsoft Certification ID (formerly, MCP ID), contact your Microsoft Regional Service Centre.
Q. I updated my email address at the Profile Centre, but it was not changed on my Microsoft Certification transcript. What is wrong?
It can take up to 48 hours for changes in your profile to appear on your Microsoft Certification transcript. Check your transcript later to verify that your email address has been updated.
Q. I entered an email address in my Microsoft Personal Profile, but the email field is still blank. What happened?
After you update your Personal Profile, a message is sent to the email address noted in your profile. For the changes to be saved, you must follow the instructions in the email message to confirm the update. Otherwise, the email address in your profile will be removed because it has not been confirmed.
Q. How do I use the Microsoft Certification logos, and what are my rights and responsibilities when I use them?
When you access the logo tool, you are required to read and accept the MCP logo guidelines to correctly promote your relationship with Microsoft and to protect the integrity of the logos. You must sign in to the benefits and exams dashboard in order to access these guidelines.
Q. How can I download electronic files of Microsoft Certification logos?
Logos are available for download from the benefits and exams dashboard.
Q. I passed a test a week ago and I want to print my logo, but I cannot select it for printing.
The test that you passed might not qualify you to print that specific logo. If you believe this is an error, contact the Microsoft Regional Service Centre.
Q. How do I report misuse of a Microsoft Certification logo?
Contact the Microsoft Regional Service Centre.
Microsoft account and Profile Centre
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Q. What is Microsoft account?
Microsoft account (formerly Windows Live ID) enables you to simply use your email address and password to sign in. After you create your Microsoft account, you can access all Microsoft account sites and services. If you already have an MSN Hotmail, MSN Messenger or Passport account, it is your Microsoft account.
Learn more about Microsoft account.
Q. If I do not have a Microsoft account, do I need to set one up to access the benefits and exams dashboard?
Yes. You can sign up for a Microsoft account now. You will not be able to access the benefits and exams dashboard without one.
Q. If I already have a Microsoft account, can I use it to access the benefits and exams dashboard?
Yes.
Q. I do not remember the Microsoft account I used to access the benefits and exams dashboard. What should I do?
If you cannot remember the Microsoft account that you used to access the benefits and exams dashboard, contact your Microsoft Regional Service Centre for assistance.
Q. Will my Microsoft account expire?
If your Microsoft account is unused for one year, your Microsoft account may expire, and you may need to re-establish a Microsoft account.
Q. How do I update my profile?
Log in to the benefits and exams dashboard and, under the Account menu in the top right corner of the page, click Profile settings.
Q. What should I regularly update in my profile?
Update the following information to ensure that you receive communications from Microsoft:
Your contact preferences: Specify whether you want to receive promotional information about Microsoft products, services and events.
Your personal information: View, add or edit your personal contact information, such as your email address, business or personal address and phone numbers.
Your business information: View, add or edit information about your job and your organisation so that we can personalise content and recommend materials that match your job, organisation or industry.
Your technology preferences: View, add or edit information about your technology interests so that we can personalise content and recommend materials that match your interests.
Q. What if I do not want to receive email messages from Microsoft?
You are under no obligation to receive email messages from Microsoft. However, if you indicate that you do not want to receive communications from Microsoft through email, you cannot receive e-newsletters, such as the MCP Flash and MCT Flash. These communications provide up-to-date information on changes in training and certification resources, such as discontinued exams, Microsoft Certified Professional (MCP) benefits and special offers.
Q. How do I ensure that I receive communications by email?
Visit the Microsoft Profile Centre to indicate that you want to receive email messages from Microsoft.
Sign in to the Microsoft Profile Center to view and update your profile
Profile Center screenshot
Click My Contact Preferences, located on either the Profile Centre home page (shown above) or on the left-hand side of the page (shown below). Select E-Mail Address, and then click Save.
Note You can always unsubscribe from selected e-newsletters. However, if you do not select the E-Mail Address option, Microsoft cannot send you any information by email, including product notifications and news.
My Contact Preferences screenshot
Sign-up for e-newsletters: Select Manage Subscriptions on the left-hand side of the page. Tick all of the subscriptions that you want to receive, and then click Subscribe. You can also unsubscribe from publications.
Accessing your transcript
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Q. Where can I find my transcript or see which exams I have passed?
Access your transcript from the benefits and exams dashboard.
Under the section called Transcript, click on the View link.
Q. How do I give my employer or others access to my transcript via a secure connection that they can trust?
Microsoft offers a tool called Transcript Sharing, which can be accessed from the benefits and exams dashboard. Under the section called Transcript, click the Share link.
You will be asked to create an Access Code (which can be changed at any time) and given a Transcript ID. You will then provide these two codes to your selected audience, along with a URL to view your transcript.
Q. I have certifications from multiple providers; can I combine all my credentials into one transcript?
Microsoft has worked with the IT Certification Council (ITCC), along with other industry certification providers, to provide MCPs with the opportunity to create one transcript across providers. Under the Transcript section of the benefits and exams dashboard, click Create a multi-vendor transcript. You will then be asked to provide your transcript sharing codes. The transcript sharing code can be found by clicking Share your transcript.
Q. What if I cannot print or access my transcript?
If you cannot print or access your transcript, contact your Microsoft Regional Service Centre.
To ensure a prompt response:
Use the email address associated with your Microsoft Certification ID (MC ID), if possible.
Have your Microsoft Certification ID number available.
If you do not know your Microsoft Certification ID, have other information available, such as your address, telephone number, exam numbers and completion dates.
Q. I viewed my transcript but it is missing data. Why can't I see all my data?
It can take up to two weeks for Microsoft to receive and process your exam records. If it has been more than two weeks since you took your exam, and the results still do not appear on your transcript, or if you notice any other problems, contact your Microsoft Regional Service Centre.
Training and certification from Microsoft
Fulfill your potential and make the most of your investment in Microsoft technology with certification, classroom training, e-learning, and books from Microsoft and Microsoft Learning Partners.
Certifications
A Microsoft Certification validates your expertise in a Microsoft technology. As a Microsoft Certified Professional, you’ll have access to community resources and tools that allow you to exchange ideas with peers, increase your knowledge and skills, and broaden your career opportunities.
Microsoft Certified Trainers
Microsoft Certified Trainers (MCTs) are classroom and e-learning instructors, training and certification consultants, authors, conference presenters, and user group leaders who combine their expertise, experience, and passion for training and leadership to help Microsoft customers and partners realize their full learning potential.
Microsoft Learning Partners
Microsoft Partners with the Learning competency (Learning Partners) are training companies that meet stringent Microsoft qualifications to train IT professionals and developers on Microsoft technologies.
Microsoft Imagine Academy
The Microsoft Imagine Academy program connects the world of education to the world of work by enabling faculty and students to acquire new technology skills in an academic setting.
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