Pass your actual test with our Microsoft DP-100日本語 training material at first attempt
Updated: Sep 04, 2026
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The DP-100 exam includes various topics related to data science, such as data exploration, data preparation, data modeling, machine learning, and data visualization. DP-100J exam also tests the candidate's knowledge of Azure services that are used for data solutions, such as Azure Machine Learning, Azure Data Factory, Azure Stream Analytics, and Azure Databricks. DP-100J exam format includes multiple-choice questions, case studies, and practical exercises.
Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Data Science Solution on Azure |
| Exam Number: | DP-100 |
| Exam Duration: | 100-120 |
| Passing Score: | 700/1000 |
| Exam Price: | USD 165 (varies by region) |
| Real Exam Qty: | 40-60 |
| Available Languages: | German, Simplified Chinese, Korean, Spanish, English, French, Japanese, Portuguese (Brazil), Russian |
| Certificate Validity Period: | 1 year (renewable through Microsoft certification renewal assessment) |
| Related Certifications: | Microsoft Certified: Azure Data Scientist Associate |
| Exam Format: | Multiple choice, Drag and drop, Multiple response, Case studies, Hands-on lab tasks |
| Recommended Training: | Microsoft Learn - DP-100 Learning Path Azure Machine Learning Documentation |
| Exam Registration: | Official Microsoft Certification Page Pearson VUE Registration |
| Sample Questions: | Microsoft DP-100日本語 Sample Questions |
| Exam Way: | Online proctored or in-person at authorized testing centers (Pearson VUE) |
| Pre Condition: | No mandatory prerequisites. Recommended familiarity with Python, machine learning concepts, and Azure fundamentals. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/azure-data-scientist/ |
Microsoft DP-100 Certification Exam covers a wide range of topics related to data science, including data exploration and visualization, data preparation, modeling, and deployment. It also covers various Azure tools and services for data science, such as Azure Machine Learning, Azure Databricks, Azure Stream Analytics, and more. DP-100J exam is designed to test your ability to design and implement end-to-end data science solutions on the Azure platform.
Microsoft DP-100 exam covers various topics related to data science, including data exploration and preparation, data modeling, machine learning algorithms, and data visualization. DP-100J exam also assesses the candidate's ability to use Azure services for data science, such as Azure Machine Learning, Azure Databricks, and Azure HDInsight. To prepare for the exam, candidates can take online courses, attend training sessions, and practice with sample questions and labs provided by Microsoft. By passing the Microsoft DP-100 exam, candidates can demonstrate their expertise in designing and implementing data science solutions on Azure, which can help them advance their career and gain recognition in the industry.
Microsoft DP-100 certification exam is an essential tool for professionals who want to enhance their skills in data science and Azure data science solutions. DP-100J exam covers a wide range of topics related to data science solutions on Azure and is designed to test the candidate’s ability to design and implement data science solutions using Azure services. The DP-100 certification exam is an excellent tool for professionals who want to advance their careers in data science and demonstrate their expertise in Azure data science solutions.
| Section | Objectives |
|---|---|
| Topic 1: Design and prepare a machine learning solution | - Manage compute and data assets - Plan and configure Azure Machine Learning workspace - Select appropriate Azure services for machine learning workloads |
| Topic 2: Explore and analyze data | - Ingest and prepare data for modeling - Perform exploratory data analysis |
| Topic 3: Train machine learning models | - Tune hyperparameters and evaluate models - Train models using Azure Machine Learning |
| Topic 4: Deploy and consume models | - Monitor deployed models and endpoints - Deploy models to endpoints |
| Topic 5: Optimize and manage models | - Track experiments and manage model lifecycle - Improve model performance |
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