How much DP-100 Exam Cost
The price of the DP-100 exam is $165 USD.
2. Train Models & Run Experiments (25-30%):
- Metrics generation from experiment runs: The candidates must be able to use logs for troubleshooting errors in experiment runs, log metrics from experiment run, and view and retrieve experiment outputs.
- Models creation with Azure ML Designer: This domain covers the examinees’ skills in using custom code modules within the design and using designer modules for the definition of pipeline data flows. It also requires one’s competence in ingesting data within designer pipelines and creating training pipelines utilizing ML Designer.
- Model training process automation: The individuals need the relevant skills in running pipelines, passing data within steps in pipelines, monitoring pipeline runs, and creating pipelines with the use of SDK.
- Training scripts run within Azure ML workspaces: The students should have the expertise in creating and running experiments utilizing Azure ML SDK as well configuring run settings for the scripts. This subject area also requires their skills in data consumption from datasets for an experiment using Azure ML SDK.
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Reference: https://www.microsoft.com/en-us/learning/exam-dp-100.aspx
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Exam Details & Skills Measured
Microsoft DP-100 is an associate-level certification exam. It can be taken as a proctored test if this option is available in your country. If it’s not, you can sit for it as an online exam at one of the Pearson VUE testing centers across the world. You should check the official webpage for more information about scheduling this exam.
When you are ready for this test, you have to pay $165 as a registration fee, which applies to a single delivery of the exam. You can take it in English, Korean, Japanese, or Simplified Chinese. Microsoft DP-100 contains 40-60 questions that cover different types, such as drag and drop, multiple choice, active screen, build list, short answer, best answer, and case studies, among others. If you want to pass this test on the first try, you should get 720 points on a scale of 100-1000.
Microsoft Designing and Implementing a Data Science Solution on Azure (DP-100 Korean Version) Sample Questions:
참고: 이 문제는 동일한 시나리오를 제시하는 일련의 문제 중 하나입니다. 각 문제에는 제시된 목표를 달성할 수 있는 고유한 해결책이 포함되어 있습니다. 일부 문제 세트에는 정답이 두 개 이상일 수 있으며, 정답이 없는 문제 세트도 있습니다.
이 섹션에서 질문에 답변한 후에는 해당 질문으로 돌아갈 수 없습니다. 따라서 이 질문들은 검토 화면에 나타나지 않습니다.
당신은 과거 데이터를 기반으로 날씨를 예측하는 모델을 만듭니다.
데이터 저장소에서 데이터를 로드하는 처리 스크립트를 실행하고, 처리된 데이터를 머신러닝 모델 학습 스크립트에 전달하는 파이프라인을 생성해야 합니다.
해결 방법: 다음 코드를 실행하세요.
이 해결책은 목표를 달성합니까?
- A. 예
- B. 아니요
Correct Answer: B 🗳️
Explanation: Only visible for PassReview members. You can sign-up / login (it's free).
Azure Machine Learning 작업 영역을 관리하고 있습니다. script.py라는 Python 스크립트는 training_data라는 인수를 읽습니다. training_data 인수는 datasetl.csv라는 파일에 있는 학습 데이터의 경로를 지정합니다. 이 스크립트를 머신 러닝 모델을 학습시키는 명령 작업으로 실행할 계획입니다.
스크립트를 학습 작업으로 제출할 때 데이터셋 경로를 매개변수 값으로 전달하는 명령어를 제공해야 합니다.
해결 방법: python script.py dataset1.csv
이 해결책은 목표를 달성합니까?
- A. 예
- B. 아니요
Correct Answer: B 🗳️
Azure AI Foundry 프로젝트가 있습니다.
텍스트와 이미지를 모두 입력으로 받을 수 있는 기본 Azure OpenAI 서비스 모델을 미세 조정하기 위해 Azure AI Foundry 포털을 사용할 계획입니다. 적합한 모델을 선택해야 하는데, 어떤 모델을 선택해야 할까요?
- A. gpt-4
- B. gpt-4o
- C. gpt-35-터보
- D. 다빈치-002
Correct Answer: A 🗳️
Azure AI Foundry 프로젝트가 있습니다. RAG 솔루션을 개발합니다.
해결책을 평가해야 합니다.
평가에 필요한 데이터가 포함된, 형식이 올바른 파일을 제공해야 합니다. 해결 방법: .jsonl 형식의 파일을 사용하십시오.
이 해결책은 목표를 달성합니까?
- A. 예
- B. 아니요
Correct Answer: B 🗳️
Azure ML SDK를 사용하여 실험을 실행하기 위해 컴퓨팅 리소스를 생성해야 합니다. 다음 코드를 실행합니다.
다음 각 문장에 대해, 문장이 사실이면 '예'를 선택하고, 그렇지 않으면 '아니요'를 선택하십시오.
참고: 정답 하나당 1점입니다.
Correct Answer:
Explanation:
Box 1: No
If a training cluster already exists it will be used.
Box 2: Yes
The wait_for_completion method waits for the current provisioning operation to finish on the cluster.
Box 3: Yes
Low Priority VMs use Azure ' s excess capacity and are thus cheaper but risk your run being pre-empted.
Box 4: No
Need to use training_compute.delete() to deprovision and delete the AmlCompute target.
Reference:
https://notebooks.azure.com/azureml/projects/azureml-getting-started/html/how-to-use-azureml/training/train- on-amlcompute/train-on-amlcompute.ipynb
https://docs.microsoft.com/en-us/python/api/azureml-core/azureml.core.compute.computetarget
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