Testing Process Details of Microsoft DP-100

As for the exam format, there are usually about 40-60 multiple-choice, active screen, best answer, hot area, build lists, labs, mark review and other question styles. You are expected to complete them in 3 hours. The passing score is 700 out of 1000 maximum possible points. The test is available in the following languages: English, Japanese, Korean, and Chinese (Simplified). To schedule your test, you should first pay the registration fee of $165 and go to the Pearson VUE platform to create an account. Once you log in, choose the “Proctored Exams” section and enter ‘DP-100' as the exam code. Follow the prompts to complete registration. At this stage, you can choose to take your test offline or online. Notice, though, that if you don't succeed on the first try, you'll be required to pay the enrollment fee for the next attempt as well.

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Knowing Associated Certification

The Microsoft DP-100 test is associated with the Microsoft Certified: Azure Data Scientist Associate certificate. It is a recently launched certification by Microsoft trying to impart the knowledge of concepts related to machine learning techniques. As a rule, earners are known to have industry-standard expertise related to evaluation and deployment models for building ML solutions. Apart from grating this noteworthy designation, the Microsoft DP-100 exam will also help the test-taker to gain some ACE college credits.

Ideal Candidate Profile

This exam will provide substantial career growth for data scientist-related job roles. If anyone’s job profile demands natural language processing and predictive analysis, s/he can aim at this exam to access needed expertise.

Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx

Microsoft DP-100: Skills Measured

Microsoft provides you with the elaborate outline of the skills that you need to acquire before attempting the test. The specific topics of the exam along with the main subtopics are enumerated below:

• Perform Feature Engineering (15%)

  Answering the questions that are drawn from this domain, the test takers should be able to perform the tasks such as performing feature selection as well as performing feature extraction.

• Define and Prepare the Development Environment (15%)

  To answer the questions within this objective, the applicants should have the professional ability to accomplish such technical tasks as selecting a development environment; quantifying the business problem; setting up a development environment; etc.

• Prepare Data for Modeling (25%)

  This subject area revolves around cleansing and transforming data; performing EDA (Exploratory Data Analysis); transforming data into usable datasets.

• Develop Models (40%)

  The skills measured within this topic include selecting an algorithmic approach; evaluating model performance; training the model; identifying data imbalances; splitting datasets, and so on.

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