Snowflake · SF-GAI · Intermediate
SnowPro Specialty: Gen AI (GES-C01) — Practice Questions and Mock Exam
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Checked against Snowflake · April 2026Current exam version
Overview
About the exam
The SnowPro Specialty: Gen AI Certification (GES-C01) validates expertise in building generative AI and large language model applications on Snowflake, including Cortex AI functions, retrieval-augmented generation (RAG) patterns, LLM fine-tuning, vector embeddings and search, Snowflake Notebooks for AI development, and responsible AI practices. It tests the ability to design and deploy production-grade AI solutions natively within the Snowflake platform.
This specialty certification is for AI engineers, ML practitioners, and data scientists with at least one year of experience building AI/ML solutions on Snowflake. It validates practical skills in the fastest-growing area of the data platform industry and positions holders at the forefront of enterprise AI adoption.
Exam Domains
What's on the exam
The exam consists of 60 questions — multiple-choice and multiple-select — to be completed in 85 minutes. Questions cover domains including Cortex AI Functions, RAG Architecture, LLM Fine-Tuning, Vector Search & Embeddings, AI Application Development, and Responsible AI. A passing score is 750 out of 1000. At 1.5 minutes per question, pacing is tight given the complexity of AI scenario questions — manage your time carefully.
Understand Snowflake Cortex capabilities, LLM integration, and Gen AI concepts within the Snowflake platform.
Use Snowflake Cortex LLM functions including COMPLETE, EXTRACT_ANSWER, SENTIMENT, SUMMARIZE, and TRANSLATE.
Implement governance, security, and compliance for Gen AI workloads in Snowflake.
SourceSnowflake exam page
Format
What to expect
Watch out
Where candidates struggle
Candidates who have used general-purpose AI tools but haven't built with Snowflake Cortex specifically often struggle with questions about COMPLETE, EMBED, and SEARCH functions and their Snowflake-native integration patterns.
- 01Cortex COMPLETE vs External — Not understanding when to use Cortex COMPLETE (native, serverless) versus calling external LLM APIs and the trade-offs of each approach leads to architecture question errors.
- 02RAG Pipeline Design — Confusing embedding generation, vector storage, similarity search, and context injection steps in a RAG pipeline causes retrieval-augmented generation question failures.
- 03Vector Data Types — Not understanding Snowflake VECTOR data type, distance metrics (cosine, inner product, L2), and how vector search integrates with Cortex leads to embedding question mistakes.
- 04Fine-Tuning vs Prompting — Not knowing when fine-tuning is appropriate versus few-shot prompting or RAG — and the cost and data requirements of each — leads to wrong solution design answers.
Details
Exam logistics
Delivered online via the Snowflake Certification Portal. Available in English. The certification is valid for 2 years. Renewal requires recertification or continuing education credits. Exam fee is $250 USD. Prerequisite: active SnowPro Core certification.
SourceSnowflake exam page
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