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Updated: Oct 05, 2026
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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: Data Engineer SnowPro Core Certification |
| Exam Format: | Multiple select, Multiple choice |
| Available Languages: | English |
| Recommended Training: | Snowflake Training and Certification Courses |
| Exam Registration: | Snowflake Certification Portal |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored exam via Snowflake certification platform or authorized testing provider |
| Pre Condition: | SnowPro Core certification is recommended; familiarity with SQL, Python, and data science workflows is expected. |
| Official Syllabus URL: | https://www.snowflake.com/certifications/ |
Snowflake DSA-C02 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Snowflake ML and Data Science Tools | - Using Snowpark for Python - Applying built-in Snowflake ML capabilities |
| Feature Engineering and Data Processing | - Feature creation and transformation techniques - Handling structured and semi-structured data |
| Data Ingestion and Data Preparation | - Data cleaning and transformation in Snowflake - Data loading and ingestion patterns |
| Model Deployment and Operationalization | - Monitoring and maintaining ML workflows - Deploying models in Snowflake environment |
| Machine Learning in Snowflake | - Model development and training workflows - Model evaluation and iteration |
Preparing for DSA-C02 with Feedback That Corrects You
- Feature Engineering and Data Processing ()
- Machine Learning in Snowflake ()
- Snowflake ML and Data Science Tools ()
Snowflake SnowPro Advanced: Data Scientist Certification Sample Questions:
The most widely used metrics and tools to assess a classification model are:
- A. Area under the ROC curve
- B. Confusion matrix
- C. Cost-sensitive accuracy
- D. All of the above
Correct Answer: D 🗳️
Mark the correct steps for saving the contents of a DataFrame to aSnowflake table as part of Moving Data from Spark to Snowflake?
- A. Step 1.Use the write() method of the DataFrame to construct a DataFrameWriter.
Step 2.Specify SNOWFLAKE_SOURCE_NAME using the format() method.
Step 3.Specify the connector options using either the option() or options() method.
Step 4.Use the dbtable option to specify the table to which data is written.
Step 5.Use the mode() method to specify the save mode for the content.
(Correct) - B. Step 1.Use the PUT() method of the DataFrame to construct a DataFrameWriter.
Step 2.Specify SNOWFLAKE_SOURCE_NAME using the format() method.
Step 3.Specify the connector options using either the option() or options() method.
Step 4.Use the dbtable option to specify the table to which data is written.
Step 5.Use the save() method to specify the save mode for the content. - C. Step 1.Use the PUT() method of the DataFrame to construct a DataFrameWriter.
Step 2.Specify SNOWFLAKE_SOURCE_NAME using the NAME() method.
Step 3.Use the dbtable option to specify the table to which data is written.
Step 4.Specify the connector options using either the option() or options() method.
Step 5.Use the save() method to specify the save mode for the content. - D. Step 1.Use the writer() method of the DataFrame to construct a DataFrameWriter.
Step 2.Specify SNOWFLAKE_SOURCE_NAME using the format() method.
Step 3.Use the dbtable option to specify the table to which data is written.
Step 4.Specify the connector options using either the option() or options() method.
Step 5.Use the save() method to specify the save mode for the content.
Correct Answer: A 🗳️
Explanation: Only visible for PrepAwayETE members. You can sign-up / login (it's free).
Which of the following method is used for multiclass classification?
- A. one vs rest
- B. one vs another
- C. loocv
- D. all vs one
Correct Answer: A 🗳️
Explanation: Only visible for PrepAwayETE members. You can sign-up / login (it's free).
Which of the Following is not type of Windows function in Snowflake?
- A. Association functions.
- B. Rank-related functions.
- C. Window frame functions.
- D. Aggregation window functions.
Correct Answer: A,D 🗳️
Explanation: Only visible for PrepAwayETE members. You can sign-up / login (it's free).
Consider a data frame df with 10 rows and index [ 'r1', 'r2', 'r3', 'row4', 'row5', 'row6', 'r7', 'r8', 'r9', 'row10'].
What does the aggregate method shown in below code do?
g = df.groupby(df.index.str.len())
g.aggregate({'A':len, 'B':np.sum})
- A. Computes length of column A and Sum of Column B values of each group
- B. Computes length of column A and Sum of Column B values
- C. Computes length of column A
- D. Computes Sum of column A values
Correct Answer: A 🗳️
Explanation: Only visible for PrepAwayETE members. You can sign-up / login (it's free).
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