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Snowflake SnowPro Advanced: Data Scientist Certification (DSA-C03) training and exam prep - the advanced credential for data science, ML and generative AI on Snowflake.
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The Snowflake SnowPro Advanced: Data Scientist Certification is an advanced, role-based credential for experienced practitioners who apply data science and machine-learning methodologies within the Snowflake ecosystem. It validates practical skill across the data science lifecycle on Snowflake - data preparation and feature engineering, model development with Snowpark ML, model deployment, operationalisation and monitoring - and, in the current version, Snowflake Cortex generative-AI and LLM capabilities. The certification is earned by one exam (DSA-C03, the current version - DSA-C02 retired after 2 March 2025): 65 questions in 115 minutes (multiple-choice and multiple-select, English), delivered via Pearson VUE. You pass with a scaled score of 750 out of 1000.
Data science and machine learning - and, increasingly, generative AI - are among the most in-demand skills, and the SnowPro Advanced: Data Scientist Certification proves you can apply them on Snowflake. It is a senior, high-value credential that employers often reimburse, and the current DSA-C03 version signals up-to-date, on-trend skills (Snowpark ML and Cortex LLMs).
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This advanced certification is for experienced Snowflake practitioners who do data science and ML: - Data scientists (Snowflake) - Machine-learning engineers - AI / applied-ML engineers - Analytics / ML practitioners - Senior data science professionals Recommended background: hands-on data science with Snowflake (Snowflake recommends about 2 years), plus an active SnowPro Core certification, which the Advanced certifications require.
How to earn it:
1. Hold an active SnowPro Core certification (required for the Advanced tier - renew Core first if it has expired).
2. Prepare with an advanced Data Scientist (DSA-C03) course with hands-on ML labs - that is what we provide.
3. Register for the exam through the...
The SnowPro Advanced: Data Scientist Certification (DSA-C03) validates your ability to develop, evaluate, and implement advanced data science solutions using the Snowflake AI Data Cloud. The exam assesses your knowledge of data preparation, feature engineering, machine learning workflows, model development, evaluation, optimization, Snowflake ML capabilities, and responsible data science practices. Understanding the exam structure and certification requirements can help you plan your preparation effectively and build confidence before the assessment. This section explains the exam pattern, question format, duration, certification requirements, key Snowflake assessment areas, and other important details you should know before taking the SnowPro Advanced: Data Scientist (DSA-C03) exam.
Exam details verified on 16 August 2026. The current SnowPro Advanced: Data Scientist exam is DSA-C03 (DSA-C02 retired after 2 March 2025): 65 questions in 115 minutes, with a scaled passing score of 750/1000. Snowflake's Advanced certifications require an active SnowPro Core certification. It is valid 2 years and renewed by a recertification exam or Snowflake's CE options. The fee is US$375 per attempt but varies by region. Confirm the current code, prerequisite, exact domains/weightings and pricing on Snowflake's site.
SnowPro Advanced: Data Scientist is aimed at experienced Snowflake practitioners who do data science and ML: - Data scientists and machine-learning engineers - AI / applied-ML engineers - Analytics / ML practitioners - Senior data science professionals Recommended background includes hands-on data science with Snowflake (about 2 years) and an active SnowPro Core certification, which the Advanced tier requires. If you are newer to Snowflake, take SnowPro Core (and consider the Associate) first, then step up to this advanced course.
