Snowflake SPS-C01 Exam Details & Actual Exam Questions
- Exam Code/Number: SPS-C01
- Exam Name/Title: Snowflake Certified SnowPro Specialty - Snowpark
- Certification Provider: Snowflake
- Corresponding Certification: Snowflake Certification
- Exam Questions: 374
- Updated On: Aug,29 2026
- Certification Level: Specialty
Snowflake Certified SnowPro Specialty - Snowpark Exam Questions
View SPS-C01 actual exam questions, answers and explanations for free.
92% student found the test questions almost same
All the information you need to pass Snowflake Certified SnowPro Specialty - Snowpark SPS-C01 exam and free practice exam verified by EduDump exam experts.
Said the test questions were almost same
Passed the exams with the material
Found the study quides effective and helpful
(50 Up Votes)Snowflake SPS-C01 Exam Overview:
| Certification Vendor: | Snowflake |
|---|---|
| Exam Name: | Snowflake Certified SnowPro Specialty - Snowpark |
| Exam Number: | SPS-C01 |
| Exam Duration: | 85 minutes |
| Exam Price: | $225 USD |
| Real Exam Qty: | 55 |
| Exam Format: | Multiple Select, Multiple Choice, Interactive |
| Passing Score: | 750 (scaled 0-1000) |
| Related Certifications: | SnowPro Core Certification |
| Available Languages: | English |
| Sample Questions: | Snowflake SPS-C01 Sample Questions |
| Exam Way: | Online Proctored or Onsite Testing Center |
| Pre Condition: | SnowPro Core Certification is required. |
| Official Syllabus URL: | https://learn.snowflake.com/en/certifications/snowpro-snowpark |
Snowflake SPS-C01 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Snowpark Concepts | 15% | - Snowpark DataFrames and query plans - Client-side vs. Server-side execution - Stored procedures and conditional logic - Snowpark architecture and core concepts - Transformations vs. Actions - Snowpark Sessions and connection management |
| Snowpark API for Python | 30% | - Establishing connections and session management - Reading and writing data - Working with Semi-structured data - User-Defined Functions (UDFs) and Stored Procedures - DataFrame creation and manipulation |
| Data Transformations and DataFrame Operations | 35% | - Window functions - Using built-in functions - Filtering, Aggregating, and Joining DataFrames - Persisting transformed data - Complex data pipelines |
| Performance Optimization and Best Practices | 20% | - Query pushdown and optimization - Warehouse sizing for Snowpark - Caching strategies - Minimizing data transfer - Debugging and explain plans - Vectorized UDFs |
0
0
0
10