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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:
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.
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.
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.
This subject area revolves around cleansing and transforming data; performing EDA (Exploratory Data Analysis); transforming data into usable datasets.
The dream of becoming a highly skilled data scientist can turn into a reality with the help of the Microsoft DP-100 exam. This exam tries to impart an associate-level understanding of data science and machine learning with an aim to generate a skilled workforce of data scientists.
Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx
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| Section | Weight | Objectives |
|---|---|---|
| Design and prepare a machine learning solution | 20-25% | - Design an Azure Machine Learning workspace
|
| Deploy and retrain models | 10-15% | - Implement retraining pipelines
|
| Explore data and train models | 35-40% | - Prepare data for modeling
|
| Prepare a model for deployment | 20-25% | - Deploy machine learning models
|
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