Exam Name: Designing and Implementing a Data Science Solution on Azure (DP-100 Korean Version)
Certification Provider: Microsoft
Corresponding Certification: Microsoft Azure
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Updated: Oct 27, 2026
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Microsoft DP-100 Korean Exam Overview:
| Certification Vendor: | Microsoft |
|---|---|
| Exam Name: | Designing and Implementing a Data Science Solution on Azure |
| Exam Number: | DP-100 |
| Related Certifications: | Microsoft Certified: Azure Data Scientist Associate |
| Available Languages: | Portuguese, Chinese (Simplified), Korean, German, Japanese, Spanish, English, French |
| Exam Price: | $165 USD |
| Real Exam Qty: | 40-60 |
| Exam Format: | Drag and Drop, Interactive Tasks, Case Study, Lab, Multiple Choice |
| Exam Duration: | 100 minutes |
| Passing Score: | 700/1000 |
| Certificate Validity Period: | 1 year |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored exam or test center delivery through Pearson VUE. |
| Pre Condition: | Candidates should have experience with Azure services, Python programming, and machine learning frameworks such as Scikit-Learn, PyTorch, or TensorFlow. |
| Official Syllabus URL: | https://learn.microsoft.com/en-us/credentials/certifications/exams/dp-100/ |
Microsoft DP-100 Korean Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Prepare a model for deployment | 20-25% | - Deploy machine learning models
|
| Topic 2: Design and prepare a machine learning solution | 20-25% | - Prepare development environments
|
| Topic 3: Explore data and train models | 35-40% | - Prepare data for modeling
|
| Topic 4: Deploy and retrain models | 10-15% | - Monitor deployed models
|
Microsoft DP-100 Korean Exam: Worthy Answers
100 minutes for 40-60 questions. Whatever your level, daily timed practice with the Lead1Pass material builds the pacing you need.
$165 USD per attempt, 700/1000 to pass. Retakes cost the full fee — value for money starts with the 528 practice questions for the DP-100 Korean exam at Lead1Pass.
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The Microsoft Designing and Implementing a Data Science Solution on Azure (DP-100 Korean Version) is Microsoft's certification exam for Microsoft Azure, at the Associate level. In drastic competition, the certificate is an explicit demonstration of your knowledge. Related credentials include Microsoft Certified: Azure Data Scientist Associate.
The Microsoft Designing and Implementing a Data Science Solution on Azure (DP-100 Korean Version) blueprint spans 4 domains — including Design and prepare a machine learning solution (20-25%), Explore data and train models (35-40%), Prepare a model for deployment (20-25%). Progress domain by domain at your own level; the complete outline above lists every subtopic.
Candidates should have experience with Azure services, Python programming, and machine learning frameworks such as Scikit-Learn, PyTorch, or TensorFlow. Eligibility rules change over time, so verify the current requirements on the official page (official DP-100 Korean exam page) before registering.
Microsoft Designing and Implementing a Data Science Solution on Azure (DP-100 Korean Version) Sample Questions:
쉼표로 구분된 값(CSV) 형식의 데이터가 포함된 파일이 있으며, 이 파일을 사용하여 분류 모델을 학습시키려고 합니다.
Azure Machine Learning Studio의 자동화된 머신 러닝 인터페이스를 사용하여 분류 모델을 학습시키고 있습니다. 작업 유형을 분류로 설정했습니다.
자동화된 머신러닝 프로세스가 선형 모델만 평가하도록 해야 합니다.
어떻게 해야 할까요?
- A. 작업 유형을 회귀 분석으로 설정합니다.
- B. 자동 특징 추출 수행 옵션을 해제합니다.
- C. 종료 기준 옵션을 측정 점수 임계값으로 설정합니다.
- D. 선형 알고리즘을 제외한 모든 알고리즘을 차단된 알고리즘 목록에 추가합니다.
- E. 딥러닝 활성화 옵션을 해제합니다.
Correct Answer: B 🗳️
Explanation: Only visible for Lead1Pass members. You can sign-up / login (it's free).
Azure Machine Learning 작업 영역을 관리합니다. 작업 영역 관리를 위한 개발 환경은 Azure Machine Learning Notebooks에서 Python SDK v2를 사용하도록 구성되어 있습니다.
현재 Synapse Spark Compute가 연결되어 있으며 시스템에서 할당한 ID를 사용하고 있습니다.
Synapse Spark Compute에서 사용자가 지정한 ID를 사용하도록 업데이트하려면 Python 코드를 사용해야 합니다.
해결 방법: DefaultAzureCredential 클래스를 초기화합니다.
이 해결책은 목표를 달성합니까?
- A. 아니요
- B. 예
Correct Answer: A 🗳️
Azure Machine Learning 작업 영역, Azure Data Factor/파이프라인, 그리고 데이터 드리프트를 감지하기 위해 예약된 시간에 실행되는 데이터 세트 모니터를 사용합니다.
데이터셋 모니터가 데이터 드리프트를 감지하면 Azure Data Factory 파이프라인을 실행하여 데이터셋을 업데이트하는 자동화된 워크플로를 구현해야 합니다. 이 솔루션은 워크플로 구성에 필요한 노력을 최소화해야 합니다.
워크플로를 어떻게 구성해야 할까요? 답변 영역에서 적절한 옵션을 선택하세요.
참고: 정답 하나당 1점입니다.
Correct Answer:
Explanation:
Azure Machine Learning 작업 영역이 있습니다. Azure Data Lake Storage Gen2 계정을 데이터 저장소로 작업 영역에 연결하려고 합니다. 작업 영역에서 Azure Data Lake Storage Gen2 계정에 대한 액세스 권한을 부여해야 합니다.
무엇을 사용해야 할까요?
- A. SAS 토큰
- B. 계정 키
- C. 관리되는 ID
- D. 서비스 주체
Correct Answer: C 🗳️
PyTorch 프레임워크를 사용하여 다중 클래스 이미지 분류 딥러닝 실험을 생성합니다. 이 실험은 GPU가 탑재된 노드가 있는 Azure Compute 클러스터에서 실행할 계획입니다.
이미지 분류 모델을 매달 재학습시키기 위해 Azure Machine Learning 서비스 파이프라인을 정의해야 합니다. 이 파이프라인은 최소한의 비용으로 실행되어야 하며, 모델 학습에 필요한 시간도 최소화해야 합니다.
어떤 세 가지 파이프라인 단계를 순서대로 실행해야 할까요? 정답을 맞추려면, 작업 목록에서 적절한 작업을 선택하여 정답 영역으로 옮기고 올바른 순서대로 배열하세요.
Correct Answer:
Explanation:
Step 1: Configure a DataTransferStep() to fetch new image data...
Step 2: Configure a PythonScriptStep() to run image_resize.y on the cpu-compute compute target.
Step 3: Configure the EstimatorStep() to run training script on the gpu_compute computer target.
The PyTorch estimator provides a simple way of launching a PyTorch training job on a compute target.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-train-pytorch
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