Failed once? That's when direction matters most. The Databricks Certified Professional Data Scientist study guide from Test4Cram turns hard work into progress — 140 practice questions with mistake-pointing simulation.
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 |
| Exam Duration: | 120 minutes |
| Available Languages: | English |
| Real Exam Qty: | 59-60 |
| Passing Score: | 70% |
| Related Certifications: | Databricks Certified Data Engineer Professional Databricks Certified Machine Learning Professional |
| Exam Price: | USD $200 (plus applicable taxes) |
| Certificate Validity Period: | 2 years |
| Exam Format: | Multiple-select, Scenario-based questions, Multiple-choice |
| Recommended Training: | Databricks Documentation Databricks Academy & Free Training |
| Exam Registration: | Official Exam Page & Registration Kryterion Scheduling Portal |
| Sample Questions: |  |
| Exam Way: | Online proctored via Kryterion or authorized test center |
| Pre Condition: | Recommended: Proficiency in Python/Scala, Apache Spark, Databricks Lakehouse Platform, and practical data science experience; no mandatory prerequisites |
| Official Syllabus URL: | https://academy.databricks.com/exam/databricks-certified-professional-data-scientist |
Databricks Databricks-Certified-Professional-Data-Scientist Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Model Management & Deployment | 20% | - Model deployment and serving on Databricks - Monitoring and interpretability - Model registry and versioning - Experiment tracking and reproducibility with MLflow |
| Model Development & Algorithms | 30% | - Regression models: linear, logistic, regularized - Tree-based models: decision trees, random forest, gradient boosting - Spark MLlib and distributed algorithms - Unsupervised methods: clustering, PCA, anomaly detection |
| Machine Learning Fundamentals | 25% | - Statistical concepts and bias-variance tradeoff - Types of machine learning: supervised, unsupervised, reinforcement - In-sample vs out-of-sample evaluation |
| Data Preparation & Feature Engineering | 25% | - Data cleaning, transformation, and validation - Feature construction, scaling, encoding, and selection - Using Databricks for data processing |
Databricks Certified Professional Data Scientist Exam FAQ — Direct Answers
Recommended: Proficiency in Python/Scala, Apache Spark, Databricks Lakehouse Platform, and practical data science experience; no mandatory prerequisites Eligibility rules do change, so confirm the current requirements on the official page (official Databricks-Certified-Professional-Data-Scientist exam page) before booking.
120 minutes for 59-60 questions. Efficiency beats exhaustion: the Test4Cram software version simulates the real test scene and scores your performance, so every practice hour moves you forward.
Yes:
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USD $200 (plus applicable taxes) per attempt, 70% to pass. Since a retake costs the full fee, prepare with direction: the 140 practice questions from Test4Cram focus your effort where the exam points are.
What is the Databricks-Certified-Professional-Data-Scientist exam, and how do I prepare efficiently?
The Databricks Certified Professional Data Scientist is Databricks's certification exam for Databricks Certified Professional Data Scientist, at the Professional level. It validates applied skills employers hire for — a credential worth the effort. Related credentials include Databricks Certified Machine Learning Professional, Databricks Certified Data Engineer Professional.
The Databricks Certified Professional Data Scientist blueprint covers 4 domains — including Model Development & Algorithms (30%), Data Preparation & Feature Engineering (25%), Machine Learning Fundamentals (25%). The weightings are your efficiency map: heavy domains first. Every subtopic appears in the outline above.
Through the vendor's official registration channels:
The Databricks Certified Professional Data Scientist is delivered Online proctored via Kryterion or authorized test center, so pick the arrangement that suits you when booking.
Yes — download the free Databricks Certified Professional Data Scientist demo and judge the question quality before paying. Every purchase stays valid for 365 days with free updates throughout, renewable afterward at 50% off.
Databricks Certified Professional Data Scientist Sample Questions:
Refer to exhibit
You are asked to write a report on how specific variables impact your client's sales using a data set provided to you by the client. The data includes 15 variables that the client views as directly related to sales, and you are restricted to these variables only. After a preliminary analysis of the data, the following findings were made: 1.
Multicollinearity is not an issue among the variables 2. Only three variables-A, B, and C-have significant correlation with sales You build a linear regression model on the dependent variable of sales with the independent variables of A, B, and C.
The results of the regression are seen in the exhibit. You cannot request additional data. what is a way that you could try to increase the R2 of the model without artificially inflating it?
- A. Create clusters based on the data and use them as model inputs
- B. Force all 15 variables into the model as independent variables
- C. Create interaction variables based only on variables A, B, and C
- D. Break variables A, B, and C into their own univariate models
Correct Answer: A 🗳️
Explanation: Only visible for Test4Cram members. You can sign-up / login (it's free).
Feature Hashing approach is "SGD-based classifiers avoid the need to predetermine vector size by simply picking a reasonable size and shoehorning the training data into vectors of that size" now with large vectors or with multiple locations per feature in Feature hashing?
- A. It is hard to understand what classifier is doing
- B. It is easy to understand what classifier is doing
- C. Is a problem with accuracy
- D. Is a problem with accuracy as well as hard to understand what classifier us doing
Correct Answer: A 🗳️
Explanation: Only visible for Test4Cram members. You can sign-up / login (it's free).
Which analytical method is considered unsupervised?
may have a trend component that is quadratic in nature. Which pattern of data will indicate that the trend in the time series data is quadratic in nature?
- A. Linear regression
- B. Naive Bayesian classifier
- C. Decision tree
- D. K-means clustering
Correct Answer: D 🗳️
Explanation: Only visible for Test4Cram members. You can sign-up / login (it's free).
A denote the event 'student is female' and let B denote the event 'student is French'. In a class of 100 students suppose 60 are French, and suppose that 10 of the French students are females. Find the probability that if I pick a French student, it will be a girl, that is, find P(A|B).
- A. 2/6
- B. 1/3
- C. 1/6
- D. 2/3
Correct Answer: C 🗳️
Explanation: Only visible for Test4Cram members. You can sign-up / login (it's free).
In which phase of the data analytics lifecycle do Data Scientists spend the most time in a project?
- A. Communicate Results
- B. Discovery
- C. Model Building
- D. Data Preparation
Correct Answer: D 🗳️
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