DP-100Microsoft Azure Data Scientist Associate is retired
Original questions written from the published objectives and cited to official documentation, never recalled exam content. How we verify, why not dumps.
- Exam code
- DP-100
- Cost
- $165USD
- Questions
- 40 to 60
- Duration
- 100minutes
- Passing score
- 700(scale 1-1000)
- Level
- Mid level
- Study guide
- How to prepare
- Format
- Multiple choice, drag-and-drop, hot area, and case studies
What the exam tests
Exam domains and official weightings
The percentage is the exam weighting; the bar is how many verified questions we hold there, so a short bar is where our bank is thin.
- Design and prepare a machine learning solution23%0 verified
- Explore data, and run experiments22%0 verified
- Train and deploy models28%0 verified
- Optimize language models for AI applications27%0 verified
What the exam actually asks you to do
Multiple choice and multiple response, plus drag-and-drop ordering, hot area items where you click a region of a screenshot, and case studies that hold one scenario across several linked questions.
Item formats
- Multiple choice
- Multiple response
- Drag and drop
- Hot area
- Case study
The highlighted formats are the ones you cannot answer from memory alone. Microsoft Learn, exam duration and question types ↗
Microsoft Azure’s free resources
Study from the source. The page below is free to read, and it is what our own questions are written from.
Official Azure Data Scientist exam page & objectives ↗Keep reading
- Azure Data Scientist exam format
How many questions, how long, what the items look like, and how long it stays valid.
- Azure Data Scientist passing score
The exact cut score, what kind of number it is, and the retake terms.
- How hard is Azure Data Scientist?
An honest difficulty read from the format, the clock and the weights.
Frequently asked questions
How has DP-100 shifted recently?
A quarter of the exam is now optimizing language models for AI applications: prompt flows, fine-tuning choices and retrieval augmented generation in Azure AI Foundry, alongside the classic Azure Machine Learning workspace material.
Is DP-100 about data science theory?
No, it is about doing data science on Azure: workspaces, compute targets, jobs and pipelines, MLflow tracking and managed endpoints. It assumes you already know what a model is and tests where the platform fits in.
Note on domain weightings
Microsoft publishes weightings as ranges. The figures here use midpoints of the official ranges from the current DP-100 study guide.