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Last Updated: Oct 06, 2026

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Databricks Databricks-Certified-Professional-Data-Scientist Exam Overview:

Certification Vendor:Databricks
Exam Name:Databricks Certified Professional Data Scientist Exam
Exam Number:Databricks-Certified-Professional-Data-Scientist
Related Certifications:Databricks Certified Machine Learning Associate
Databricks Certified Machine Learning Professional
Databricks Certified Associate Data Scientist
Real Exam Qty:60
Exam Price:USD 200
Certificate Validity Period:2 years
Exam Format:Scenario-Based Questions, Online Proctored Exam, Multiple Select, Multiple Choice
Passing Score:70%
Available Languages:English
Exam Duration:120 minutes
Sample Questions: DOWNLOAD DEMO
Exam Way:Online proctored exam delivered through Databricks certification platform.
Pre Condition:No mandatory prerequisite. Databricks recommends prior hands-on experience with machine learning workflows, MLflow, model deployment, and Databricks Lakehouse Platform.
Official Syllabus URL:https://www.databricks.com/learn/certification

Databricks Databricks-Certified-Professional-Data-Scientist Exam Syllabus Topics:

SectionWeightObjectives
Machine Learning Development30%- Model evaluation
  • 1. Experiment tracking
  • 2. Performance metrics
  • 3. Model selection
- Model training
  • 1. Hyperparameter tuning
  • 2. Supervised learning workflows
  • 3. Cross-validation
ML Lifecycle Management20%- MLflow
  • 1. Experiment management
  • 2. Model versioning
  • 3. Model registry
- Reproducibility
  • 1. Managing artifacts
  • 2. Environment management
  • 3. Tracking runs
Governance and MLOps15%- MLOps practices
  • 1. Model monitoring
  • 2. CI/CD for machine learning
  • 3. Operational best practices
- Governance
  • 1. Access control
  • 2. Data lineage
  • 3. Unity Catalog integration
Model Deployment and Serving15%- Production operations
  • 1. Performance tracking
  • 2. Monitoring predictions
  • 3. Deployment validation
- Deployment strategies
  • 1. Model endpoints
  • 2. Real-time serving
  • 3. Batch inference
Data Exploration and Preparation20%- Data profiling
  • 1. Data quality assessment
  • 2. Feature identification
  • 3. Exploratory data analysis
- Data preparation
  • 1. Data transformation
  • 2. Data cleansing
  • 3. Feature engineering

Before You Take the Databricks Databricks-Certified-Professional-Data-Scientist Exam: Key FAQs

Registering for the Databricks-Certified-Professional-Data-Scientist exam costs USD 200 at the official rate, and you need 70% to pass. Bear in mind that an unsuccessful attempt is not discounted the second time around — a retake is charged at the full fee again. That is why experienced candidates test themselves with the 140 practice questions from SureTorrent until their results are consistently strong before spending money on the real thing.

Yes, and we encourage it. A free PDF demo of the Databricks-Certified-Professional-Data-Scientist questions is available so you can evaluate the quality and layout before buying. After purchase, your material stays current with 365 days of free updates — and if that period ever expires, you can extend the update service at a 50% discount through your member zone.

You will face 60 questions within a time allowance of 120 minutes. Raw numbers aside, the real skill is pacing: candidates who run out of time usually spent too long on early questions. Our advice is to set a mental per-question budget, skip and revisit anything that stalls you, and complete at least two full timed runs in the SureTorrent test engine before the real appointment so the clock never rattles you.

Both situations are covered. Take the corresponding Databricks-Certified-Professional-Data-Scientist exam within 60 days of purchase without passing, and you may claim a full refund under our 100% Money Back Guarantee: submit a scanned exam enrollment slip plus the official Score Report PDF within 2 days of your exam date, and we finish processing within 7 days. The conditions are strict — an exam taken within 3 days of purchase does not qualify, the candidate's name must match the payer's, and free materials or expired orders are excluded. Would you rather keep studying? Swap the order for two other exam products of equal value free of charge while keeping updates on your original purchase. As for delivery, it is immediate: files unlock for download the moment payment clears, a copy reaches your mailbox within a minute, and there is no cap on how many computers you install it on — if 2 hours pass with nothing received, contact our support team.

Passing the Databricks-Certified-Professional-Data-Scientist exam earns you the Databricks Certification certification, a Professional-level credential. It is the vendor's official proof that your skills meet the standard employers look for, and it regularly appears as a requirement in job postings. The certification also relates to Databricks Certified Associate Data Scientist, Databricks Certified Machine Learning Associate, Databricks Certified Machine Learning Professional, so it can anchor a broader certification plan rather than stand alone.

No mandatory prerequisite. Databricks recommends prior hands-on experience with machine learning workflows, MLflow, model deployment, and Databricks Lakehouse Platform. Because vendors revise their eligibility rules from time to time, treat this as a starting point and verify the latest requirements on the official exam page — see the official Databricks-Certified-Professional-Data-Scientist exam outline before you commit to a test date.

The vendor organizes the Databricks Certified Professional Data Scientist blueprint into 5 domains, led by Machine Learning Development (30%), Governance and MLOps (15%), Data Exploration and Preparation (20%). Every domain contains further subtopics, and the weighting tells you where your study hours pay off most — the full outline above has the complete picture, so review it before building your study plan.

Databricks Certified Professional Data Scientist Sample Questions:

Question #1

Suppose you have been given a relatively high-dimension set of independent variables and you are asked to come up with a model that predicts one of Two possible outcomes like "YES" or "NO", then which of the following technique best fit.

  • A. Random decision forests
  • B. Naive Bayes
  • C. Logistic regression
  • D. All of the above
  • E. Support vector machines
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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Question #2

Of all the smokers in a particular district, 40% prefer brand A and 60% prefer brand B.Of those smokers who prefer brand A. 30% are females, and of those who prefer brand B.40% are female. What is the probability that a randomly selected smoker prefers brand A, given that the person selected is a female?
Which of the following is a best way to solve this problem?

  • A. Bays Theorem
  • B. None of the above
  • C. Poisson Distribution
  • D. Binomial Distribution
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

Question #3

You are using one approach for the classification where to teach the agent not by giving explicit categorizations, but by using some sort of reward system to indicate success, where agents might be rewarded for doing certain actions and punished for doing others. Which kind of this learning

  • A. Unsupervised
  • B. None of the above
  • C. Supervised
  • D. Regression
Reveal Solution  Discussion  0

Correct Answer: A  🗳️

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Question #4

You are working with the Clustering solution of the customer datasets. There are almost 40 variables are available for each customer and almost 1.00,0000 customer's data is available. You want to reduce the number of variables for clustering, what would you do?

  • A. You cannot discard any variable for creating clusters.
  • B. You will find the correlation among the variables and from their variables are not co-related will be discarded.
  • C. You can combine several variables in one variable
  • D. You will randomly reduce the number of variables
  • E. You will find the correlation among the variables and from the highly co-related variables, you will be considering only one or two variables from it.
Reveal Solution  Discussion  0

Correct Answer: C,E  🗳️

Explanation: Only visible for SureTorrent members. You can sign-up / login (it's free).

Question #5

Suppose that we are interested in the factors that influence whether a political candidate wins an election. The outcome (response) variable is binary (0/1); win or lose. The predictor variables of interest are the amount of money spent on the campaign, the amount of time spent campaigning negatively and whether or not the candidate is an incumbent.
Above is an example of

  • A. Hierarchical linear models
  • B. Maximum likelihood estimation
  • C. Linear Regression
  • D. Logistic Regression
  • E. Recommendation system
Reveal Solution  Discussion  0

Correct Answer: D  🗳️

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