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The benefit in Obtaining the DP-100 Exam Certification
- Organization owners invest a lot in their employees when it comes to their training with the goal of making them quicker, more efficient, and more knowledgeable about their role. Certified Professional will reduce the time he spends on tasks, meaning he can get more done this could help reduce company downtime when repairing faults on a system or fixing hardware problems.
- Becoming Microsoft Certified Azure Data Scientist Associate means one thing you are worth more to the company and therefore more to yourself in the form of an upgraded pay package. On average a Microsoft Certified Azure Data Scientist Associate member of staff is estimated to be worth 30% more to a company than their uncertified professionals.
- When Candidates applying for a job or looking to promotion in their current position, a Microsoft Certified Azure Data Scientist Associate certification in the field in which Candidates are applying will put you at the top of the list and make them a desirable candidate for employers.
- After completion of Microsoft Certified Azure Data Scientist Associate Certification candidates receive official confirmation from Microsoft that you are now fully certified in their chosen field. This can be now added to their CV, cover letters and job applications.
- Candidates will get in-depth knowledge by completing the courses along with the access to revision materials for 6 months upon completion means they will have a wider skill set when it comes to the various technologies and systems than an uncertified professional. Certified Professional in this particular skill set is 74% more efficient when it comes to completing their tasks in a timely well-executed manner.
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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:
- 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.
- 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.
- 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.
Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx
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Career Opportunities & Salary Outlook
The demand for the certified professionals is on the increase. As an Azure Data Scientist, you can explore many employment opportunities. So, if you want to boost your career potential, pursuing the Microsoft Certified: Azure Data Scientist Associate certification is the right step. To get this certificate, you have to pass the qualifying exam, which is Microsoft DP-100. With this associate-level certification, you can get the positions, such as a Data Scientist, a Senior Data Scientist, a Data Science Manager, and a Data Science Director. The average salary for these job roles is $135,000 per annum. With advanced experience, the specialists can earn up to $170,000 per year.
The Microsoft DP-100 test helps candidates check their machine learning knowledge and skills and prove themselves as qualified data scientists.
Microsoft DP-100日本語 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Explore data and train models | 35-40% | - Run experiments and train models
|
| Deploy and retrain models | 10-15% | - Monitor deployed models
|
| Design and prepare a machine learning solution | 20-25% | - Design an Azure Machine Learning workspace
|
| Prepare a model for deployment | 20-25% | - Manage deployment assets
|


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