Exam Name: Databricks Certified Professional Data Scientist Exam
Certification Provider: Databricks
Corresponding Certification: Databricks Certification
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The Databricks-Certified-Professional-Data-Scientist exam can feel demanding because it tests more than simple recall. In 2026, Actual4dump gives candidates preparing for Databricks Certified Professional Data Scientist a practical way to turn the objectives into 140 structured practice opportunities.
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 |
| Real Exam Qty: | 60 |
| Related Certifications: | Databricks Certified Machine Learning Professional Databricks Certified Associate Data Scientist Databricks Certified Machine Learning Associate |
| Exam Price: | USD 200 |
| Exam Format: | Scenario-Based Questions, Online Proctored Exam, Multiple Select, Multiple Choice |
| Certificate Validity Period: | 2 years |
| Exam Duration: | 120 minutes |
| Passing Score: | 70% |
| Available Languages: | English |
| 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:
| Section | Weight | Objectives |
|---|---|---|
| ML Lifecycle Management | 20% | - MLflow
|
| Model Deployment and Serving | 15% | - Production operations
|
| Machine Learning Development | 30% | - Model evaluation
|
| Governance and MLOps | 15% | - MLOps practices
|
| Data Exploration and Preparation | 20% | - Data profiling
|
Frequently Asked Questions for the Databricks Databricks-Certified-Professional-Data-Scientist Exam
The Databricks-Certified-Professional-Data-Scientist exam, Databricks Certified Professional Data Scientist Exam, assesses whether a candidate can apply Databricks knowledge to the skills measured by this credential. It is associated with the Databricks Certification certification. The certification is positioned at the Professional level. Related credentials include Databricks Certified Associate Data Scientist, Databricks Certified Machine Learning Associate, Databricks Certified Machine Learning Professional.
The Databricks-Certified-Professional-Data-Scientist exam includes 60 questions and allows 120 minutes. Plan your pacing before exam day rather than calculating it under pressure. Timed sessions with Actual4dump practice tests can help you decide when to flag a difficult item, keep moving, and reserve enough time for a final review.
The published passing score for Databricks Certified Professional Data Scientist is 70%, and the official exam fee is USD 200. A retake requires budgeting for the full official fee again, so it is sensible to complete several timed practice tests before scheduling. Consistent results across the 140 practice questions can give you a clearer picture of your readiness.
The stated prerequisite information for Databricks Certified Professional Data Scientist is: No mandatory prerequisite. Databricks recommends prior hands-on experience with machine learning workflows, MLflow, model deployment, and Databricks Lakehouse Platform. Before registering, review the eligibility details on the official exam page to confirm the requirements.
Yes. Actual4dump provides a free PDF demo so you can review the format and quality of the Databricks Certified Professional Data Scientist practice questions before placing an order. Your purchase includes 365 days of free updates, and you can extend the update service after expiration at a 50% discount.
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Delivery is instant after payment. Your download is also sent to your email within one minute; if it has not arrived within 2 hours, contact customer service. There is no limit on the number of computers on which the material can be installed.
The published Databricks Certified Professional Data Scientist outline contains 5 major domains. The opening domains include:
- Machine Learning Development (30%)
- Governance and MLOps (15%)
- Model Deployment and Serving (15%)
Review the complete Exam Topics section above for every domain and subtopic before planning your study time.
Databricks Certified Professional Data Scientist Sample Questions:
Question 1
Which of the following is not a correct application for the Classification?
A. credit scoring
B. image recognition
C. tumor detection
D. drug discovery
Question 2
Question-3: In machine learning, feature hashing, also known as the hashing trick (by analogy to the kernel trick), is a fast and space-efficient way of vectorizing features (such as the words in a language), i.e., turning arbitrary features into indices in a vector or matrix. It works by applying a hash function to the features and using their hash values modulo the number of features as indices directly, rather than looking the indices up in an associative array. So what is the primary reason of the hashing trick for building classifiers?
A. It requires the lesser memory to store the coefficients for the model
B. It reduces the non-significant features e.g. punctuations
C. Noisy features are removed
D. It creates the smaller models
Question 3
In which phase of the analytic lifecycle would you expect to spend most of the project time?
A. Operationalize
B. Data preparation
C. Discovery
D. Communicate Results
Question 4
You are asked to create a model to predict the total number of monthly subscribers for a specific magazine.
You are provided with 1 year's worth of subscription and payment data, user demographic data, and 10 years worth of content of the magazine (articles and pictures). Which algorithm is the most appropriate for building a predictive model for subscribers?
A. TF-IDF
B. Decision trees
C. Linear regression
D. Logistic regression
Question 5
In statistics, maximum-likelihood estimation (MLE) is a method of estimating the parameters of a statistical model. When applied to a data set and given a statistical model, maximum-likelihood estimation provides estimates for the model's parameters and the normalizing constant usually ignored in MLEs because
A. The normalizing constant doesn't impact the maximizing value
B. The normalizing constant is often zero and can cause division by zero
C. The normalizing constant only has a small impact on the maximum likelihood
D. The normalizing constant is always very close to 1
Solutions:
| Question 1 Answer: D | Question 2 Answer: A | Question 3 Answer: B | Question 4 Answer: C | Question 5 Answer: A |
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