Snowflake DSA-C02 Dumps Updated – V9.03 is Good for SnowPro Advanced: Data Scientist Exam Preparation

When preparing for the SnowPro Advanced: Data Scientist Certification Exam (DSA-C02), it is crucial to ensure that you have the latest study materials to enhance your chances of success. DumpsBase offers real Snowflake DSA-C02 exam dumps that have been meticulously crafted to cover all the necessary topics. The recently updated version, V9.03, includes correct questions and answers, ensuring that you are well-prepared for the exam. With the Snowflake DSA-C02 dumps V9.03 at your disposal, you can confidently approach your certification journey. These reliable study materials increase your chances of achieving your desired outcome and pave the way for well-paying jobs and promotions in the field of data science.

Read Snowflake DSA-C02 Free Dumps Below to Check SnowPro Advanced: Data Scientist Dumps V9.03

1. Which type of Machine learning Data Scientist generally used for solving classification and regression problems?

2. Which of the learning methodology applies conditional probability of all the variables with respective the dependent variable?

A. Reinforcement learning

B. Unsupervised learning

C. Artificial learning

D. Supervised learning

3. In a simple linear regression model (One independent variable), If we change the input variable by 1 unit.

How much output variable will change?

4. There are a couple of different types of classification tasks in machine learning, Choose the Correct Classification which best categorized the below Application Tasks in Machine learning?

・ To detect whether email is spam or not

・ To determine whether or not a patient has a certain disease in medicine.

・ To determine whether or not quality specifications were met when it comes to QA (Quality Assurance).

5. Which of the following method is used for multiclass classification?

6. Which ones are the key actions in the data collection phase of Machine learning included?

A. Label

B. Ingest and Aggregate

C. Probability

D. Measure

7. Which ones are the type of visualization used for Data exploration in Data Science?

A. Heat Maps

B. Newton AI

C. Feature Distribution by Class

D. 2D-Density Plots

E. Sand Visualization

8. Which one is not the feature engineering techniques used in ML data science world?

9. Skewness of Normal distribution is ___________

10. What is the formula for measuring skewness in a dataset?

11. What Can Snowflake Data Scientist do in the Snowflake Marketplace as Provider?

12. What Can Snowflake Data Scientist do in the Snowflake Marketplace as Consumer?

13. Which one is the incorrect option to share data in Snowflake?

14. Data providers add Snowflake objects (databases, schemas, tables, secure views, etc.) to a share using.

Which of the following options?

15. Secure Data Sharing do not let you share which of the following selected objects in a database in your account with other Snowflake accounts?

16. Which one is incorrect understanding about Providers of Direct share?

17. As Data Scientist looking out to use Reader account, Which ones are the correct considerations about Reader Accounts for Third-Party Access?

A. Reader accounts (formerly known as “read-only accounts”) provide a quick, easy, and cost-effective way to share data without requiring the consumer to become a Snowflake customer.

B. Each reader account belongs to the provider account that created it.

C. Users in a reader account can query data that has been shared with the reader account, but cannot perform any of the DML tasks that are allowed in a full account, such as data loading, insert, update, and similar data manipulation operations.

D. Data sharing is only possible between Snowflake accounts.

18. SHOW GRANTS OF SHARE product_s;

19. Which object records data manipulation language (DML) changes made to tables, including inserts, updates, and deletes, as well as metadata about each change, so that actions can be taken using the changed data of Data Science Pipelines?

20. Which are the following additional Metadata columns Stream contains that could be used for creating Efficient Data science Pipelines & helps in transforming only the New/Modified data only?


 

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