SnowPro Specialty: Gen AI (GES-C01) Exam Prep

This course contains the use of artificial intelligence.

Built by Aseem Mankotia for data engineers, AI/ML engineers, and Snowflake practitioners, this exam-focused preparation course walks through every objective group of Snowflake's SnowPro Specialty: Gen AI exam (GES-C01) in exam-domain order. You will work through Snowflake Gen AI and LLM fundamentals, then go deep on Cortex AI - Cortex LLM functions like COMPLETE, SUMMARIZE, and TRANSLATE, Cortex Search for retrieval and RAG, Cortex Analyst for natural-language analytics on structured data, and Cortex Fine-Tuning for customizing hosted models. Each chapter maps directly to a named domain, calls out heavily tested concepts, and includes a hands-on read-through lab so you can trace real SQL, YAML, and application code without needing a paid Snowflake account.

Beyond Cortex, you will cover embeddings and vector search, chunking and RAG design patterns, Snowpark Container Services for custom and open-source models, Streamlit in Snowflake for building end-to-end Gen AI applications, and the governance, security, and cost controls that apply once these workloads run in production. The course reflects the exam outline updated effective March 1, 2026, which de-emphasizes Document AI, and keeps that topic intentionally light. The final chapter is a full timed exam simulation with a domain-by-domain time-management strategy so you walk into the real assessment with a clear plan. Exam format details - question count of roughly 65, duration near 85 minutes, a scaled score around 750 out of 1000, the exam fee of approximately USD 225, and the exact current exam code - are approximate throughout this course; always confirm the current SnowPro Specialty: Gen AI exam guide on Snowflake's official certification page before you register or schedule.

AI content disclosure: This course was produced with the assistance of artificial intelligence tools. Lecture narration is AI-voice generated, and lecture scripts, slides, and practice questions were drafted with AI assistance, then reviewed and curated by the instructor for technical accuracy and alignment with the official GES-C01 exam guide.