Prepare with Snowflake : DSA-C02 exam braindumps as your best preparation materials
Last Updated: Oct 11, 2026
No. of Questions: 67 Questions & Answers with Testing Engine
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Snowflake DSA-C02 Exam Overview:
| Certification Vendor: | Snowflake |
|---|---|
| Exam Name: | SnowPro Advanced: Data Scientist Certification Exam |
| Exam Number: | DSA-C02 |
| Related Certifications: | SnowPro Advanced Certifications Series SnowPro Core Certification |
| Available Languages: | English |
| Exam Format: | Scenario-Based, Multiple Select, Multiple Choice |
| Exam Duration: | 115 minutes |
| Certificate Validity Period: | 3 years |
| Real Exam Qty: | 65 |
| Passing Score: | 750 (scaled 0-1000) |
| Exam Price: | 375 USD |
| Recommended Training: | Snowflake Academy Snowflake Official Study Guide |
| Exam Registration: | Snowflake Certification Portal Pearson VUE Registration |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored (OnVUE) or in-person at Pearson VUE test centers |
| Pre Condition: | Active SnowPro Core Certification; Recommended: 2+ years hands-on Snowflake data science experience, proficiency in SQL, Python, or R |
| Official Syllabus URL: | https://learn.snowflake.com/en/certifications/snowpro-advanced-datascientist/ |
Snowflake DSA-C02 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Pipelining | 15-20% | - Data sharing and access control - Data ingestion and integration - Pipeline reliability and scalability - Snowpark and data flow orchestration |
| Model Development | 15-20% | - Using Snowflake ML and external frameworks - Model evaluation and validation - Model selection and training - Hyperparameter tuning - GenAI and LLM integration |
| Model Deployment & MLOps | 15-20% | - MLOps governance and lineage - Cost and performance optimization - Model monitoring and performance tracking - Model deployment options in Snowflake - Batch and real-time inference |
| Data Science Concepts | 15-20% | - ML problem types and use cases - Machine learning lifecycle - Statistical fundamentals - Snowflake architecture for data science |
| Data Preparation and Feature Engineering | 30-35% | - Handling missing values and outliers - Feature stores and versioning - Data cleaning and validation - Feature creation and transformation - Exploratory data analysis |
DSA-C02 Exam Material FAQ
One complete message, sent within about a minute of payment: the download link for your material, plus the account and password you need to access it. Nothing else to wait for — you can open the DSA-C02 practice questions moments after checkout.
Is there recommended training for the Snowflake SnowPro Advanced: Data Scientist Certification exam?
Many candidates combine practice questions with official training. Recommended options include:
This package includes 67 practice questions for the Snowflake SnowPro Advanced: Data Scientist Certification exam. Every answer is verified by an experienced team of experts, so you can trust what you study.
The Snowflake SnowPro Advanced: Data Scientist Certification practice questions are organized around the official exam objectives. Key topics include:
- Data Preparation and Feature Engineering (30-35%)
- Data Science Concepts (15-20%)
- Data Pipelining (15-20%)
Clear topic organization makes the material easy to navigate from day one.
The Snowflake SnowPro Advanced: Data Scientist Certification exam contains 65 questions, and you will have 115 minutes minutes to complete them. Practicing within these limits turns pacing into second nature.
The Snowflake SnowPro Advanced: Data Scientist Certification exam requires a score of 750 (scaled 0-1000) to pass, and the official registration fee is 375 USD. Planning around both figures keeps your preparation grounded.
You can register for the Snowflake SnowPro Advanced: Data Scientist Certification exam through the official channels:
Directly. Suggestions and criticism from candidates feed into our review process, and recurring points are addressed in updates to the question bank and the software. If you notice something that could be better — a confusing question, a rough edge in the engine — tell us; that input is part of how the product improves.
Active SnowPro Core Certification; Recommended: 2+ years hands-on Snowflake data science experience, proficiency in SQL, Python, or R
You can confirm the current eligibility requirements on the official DSA-C02 exam page before you register.
Snowflake SnowPro Advanced: Data Scientist Certification Sample Questions:
Select the Data Science Tools which are known to provide native connectivity to Snowflake?
- A. Denodo
- B. DiYotta
- C. DvSUM
- D. HEX
Correct Answer: D 🗳️
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Which of the learning methodology applies conditional probability of all the variables with respec-tive the dependent variable?
- A. Reinforcement learning
- B. Supervised learning
- C. Artificial learning
- D. Unsupervised learning
Correct Answer: A 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
Data providers add Snowflake objects (databases, schemas, tables, secure views, etc.) to a share us-ing Which of the following options?
- A. Grant privileges on objects to a share via a third-party role.
- B. Grant privileges on objects directly to a share.
- C. Grant privileges on objects to a share via a database role.
- D. Grant privileges on objects to a share via Account role.
Correct Answer: B,C 🗳️
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Which of the following cross validation versions is suitable quicker cross-validation for very large datasets with hundreds of thousands of samples?
- A. Leave-one-out cross-validation
- B. All of the above
- C. Holdout method
- D. k-fold cross-validation
Correct Answer: C 🗳️
Explanation: Only visible for BraindumpQuiz members. You can sign-up / login (it's free).
Which of the following process best covers all of the following characteristics?
Collecting descriptive statistics like min, max, count and sum.
Collecting data types, length and recurring patterns.
Tagging data with keywords, descriptions or categories.
Performing data quality assessment, risk of performing joins on the data.
Discovering metadata and assessing its accuracy.
Identifying distributions, key candidates, foreign-key candidates,functional dependencies, embedded value dependencies, and performing inter-table analysis.
- A. Data Visualization
- B. Data Virtualization
- C. Data Collection
- D. Data Profiling
Correct Answer: D 🗳️
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