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SnowPro Advanced Data Scientist (DSA-C03) Exam Questions 2025

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  • Contains 359 Questions
  • Total Mock Exams: 6
  • Taken exclusively from the previous real exams.
  • Last updated: 15-Sep-2025
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SnowPro Advanced Data Scientist (DSA-C03) Exam Questions 2025

  • We are offering 359 latest real SnowPro Advanced Data Scientist (DSA-C03) Exam Questions 2025  for practice, which will help you to score higher in your exam.
  • Aim for above 85% or above in our mock exams before giving the main exam. 
  • Do review wrong & right answers and thoroughly go through explanations provided to each question which will help you understand the question.
  • Weekly updates: We have a dedicated team updating our question bank on a regular basis, based on the feedback of students on what appeared on the actual exam, as well as through external benchmarking.

The SnowPro® Advanced: Data Scientist (DSA-C03) certification is designed for professionals seeking to validate their expertise in applying data science methodologies within the Snowflake ecosystem. Below are the key details and preparation resources for this certification:


Exam Overview

  • Exam Code: DSA-C03

  • Duration: 115 minutes

  • Number of Questions: 65

  • Passing Score: 750 (scaled scoring from 0–1000)

  • Cost: $375 USD

  • Delivery Method: Online proctored via Pearson VUE

  • Prerequisites: Active SnowPro® Core certification


Recommended Experience

Snowflake recommends that candidates have at least two years of hands-on experience as a data scientist in a production environment using Snowflake. Familiarity with programming languages such as Python, R, SQL, or PySpark is also beneficial.


Exam Domains

The DSA-C03 exam assesses the following domains:

  1. Data Science Concepts

    • Understanding of statistical methods, machine learning algorithms, and data preprocessing techniques.

  2. Snowflake Data Science Best Practices

    • Implementation of best practices for data science workflows within the Snowflake platform.

  3. Data Preparation and Feature Engineering

    • Techniques for preparing data and engineering features to enhance model performance.

  4. Model Training and Evaluation

    • Training machine learning models and evaluating their performance using appropriate metrics.

  5. GenAI and LLM Capabilities

    • Utilization of Generative AI and Large Language Model capabilities within Snowflake for advanced analytics.

Know more about the exam : https://learn.snowflake.com/en/certifications/snowpro-advanced-datascientistC03/

Checkout Other Snowflake Certification Exam Questions here : https://skillcertpro.com/product-category/snowflake/

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