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Snowflake SnowPro Advanced Data Scientist Quick Facts
The Snowflake SnowPro Advanced Data Scientist certification empowers data professionals to demonstrate their ability to turn raw data into actionable intelligence. This exam overview provides clarity and direction so you can approach your certification journey with confidence and focus.
How does the Snowflake SnowPro Advanced Data Scientist certification build your expertise?
This certification validates your advanced data science skills within the Snowflake ecosystem, emphasizing machine learning workflows, feature engineering, model development, and deployment best practices. It is designed for data scientists who want to showcase their ability to leverage Snowflake’s native features alongside familiar tools like Python, Snowpark, and open-source frameworks. Earning this credential shows you have the practical skills to design, train, and operationalize machine learning models at scale, all while delivering meaningful business outcomes.
Who should pursue the Snowflake SnowPro Advanced Data Scientist Certification?
The SnowPro Advanced: Data Scientist Certification is designed for experienced data scientists and machine learning professionals who want to showcase their ability to apply advanced analytics and AI capabilities within Snowflake’s Data Cloud.
You are the ideal candidate if you:
- Have 2+ years of hands-on experience with Snowflake in a production environment.
- Work with Python, R, SQL, PySpark, or Scala for data science workloads.
- Want to demonstrate your ability to train, evaluate, and deploy ML and GenAI models directly within Snowflake.
This certification elevates your profile, setting you apart as someone who can not only perform advanced analytics but also drive enterprise-scale AI innovation on the Snowflake platform.
What career opportunities does the SnowPro Advanced Data Scientist exam unlock?
Earning this certification highlights your ability to lead complex machine learning and AI projects. It opens doors to roles such as:
- Data Scientist (Snowflake-focused)
- Machine Learning Engineer
- AI Engineer
- Applied Scientist
- Advanced Analytics Specialist
- Data Science Consultant
Beyond technical opportunities, this certification can also position you for leadership roles where expertise in generative AI, MLOps, and scalable data science frameworks helps drive data strategy across organizations.
What is the latest exam version and code for this certification?
The current version of the exam is DSA-C03. This is the latest release of the SnowPro Advanced: Data Scientist exam blueprint. As Snowflake evolves its capabilities, especially around GenAI and LLM functionalities, this version reflects those innovations as part of the exam.
By preparing for DSA-C03, you are studying the most up-to-date exam format and aligning with Snowflake’s latest data science best practices.
How long is the SnowPro Advanced Data Scientist exam?
You will have 115 minutes to complete the exam. This time is designed to allow you to carefully work through the 65 exam questions, which include multiple-choice, multiple-select, and interactive formats.
With proper preparation, candidates often find this time sufficient to think critically about scenario-based questions while still pacing themselves comfortably.
How many questions are included on the Snowflake DSA-C03 exam?
The exam consists of 65 questions that test your ability across all four key domains. The questions blend practical scenarios with theoretical knowledge, ensuring you not only understand Snowflake concepts but also how to apply them in enterprise-scale data science projects.
Some questions may be unscored and used for exam research purposes, but you will not be able to tell which they are. This makes it important to give your best effort on every question.
What is the passing score for the Snowflake SnowPro Advanced Data Scientist exam?
To pass, you’ll need a scaled score of 750 out of 1000. Because Snowflake uses scaled scoring, this means even if you are weaker in certain domains, strong performance in others can balance out.
This scoring approach rewards a solid overall understanding of data science concepts and Snowflake capabilities without penalizing you for small knowledge gaps.
How much does the exam cost to take?
The exam fee is $375 USD worldwide, with a discounted price of $300 USD for those registering in India.
When considering the potential career advantage and credibility this certification brings, it’s a powerful investment in your career growth.
What language is the Snowflake SnowPro Advanced Data Scientist exam available in?
The exam is available in English only. Candidates preparing globally should be comfortable with technical terminology in English, particularly around machine learning and analytics.
What knowledge areas should I focus on while preparing?
The certification exam blueprint breaks down into four domains:
-
Data Science Concepts (17%)
- Machine learning fundamentals and supervised vs. unsupervised learning
- ML lifecycle, evaluation techniques, and statistical principles
-
Data Preparation and Feature Engineering (27%)
- Cleaning, aggregating, and transforming data in Snowflake
- Exploratory analysis with SQL and Snowpark
- Normalization, encoding, and feature creation
-
Model Development (31%)
- Training ML models in Snowflake with Snowpark and external tools
- Leveraging Snowflake Cortex for LLMs, embeddings, and fine-tuning
- Hyperparameter tuning, pipelines, metrics, and interpretability
-
Model Deployment (25%)
- Deploying ML/GenAI models via UDFs and Snowflake Model Registry
- Handling model drift, automation of retraining, and lifecycle management
Snowflake emphasizes practical understanding of model management, feature engineering, and advanced ML workflows rather than just theory.
How difficult is the DSA-C03 exam?
This is an advanced certification, but with solid practical experience and structured study, it is very attainable. It evaluates your skills in applying data science to real-world Snowflake environments.
If you have already worked with Snowpark, Snowflake ML functions, and model deployment strategies, you’ll find the scenarios highly relevant to your daily work.
What types of questions appear on the exam?
The exam includes:
- Multiple-choice questions (one correct answer)
- Multiple-select questions (two or more correct answers)
- Interactive scenario-style questions that test practical application
These formats are designed to show your actual problem-solving and analytical approach, rather than simple memorization.
Is there a prerequisite before taking the SnowPro Advanced Data Scientist exam?
Yes. To register for this exam, you must hold an active SnowPro Core Certification. The SnowPro Core ensures all advanced test takers have an established foundation in Snowflake’s architecture and ecosystem.
How is the exam structured across different topics?
The exam domains are weighted as follows:
- Data Science Concepts – 17%
- Data Preparation and Feature Engineering – 27%
- Model Development – 31%
- Model Deployment – 25%
This weighting highlights the importance of being hands-on with model development and feature engineering, which together form well over half of the exam.
Where can I take the exam?
You have two options for delivery:
- Online proctored exam — take it from your home or office with a stable internet connection.
- Onsite testing center — sit for the exam at an authorized Pearson VUE testing facility.
Both methods are equally recognized, so you can choose whichever environment helps you perform most confidently.
What are common mistakes candidates make and how can I avoid them?
Some candidates underestimate key areas such as:
- Feature Engineering — Proper handling of missing values, encoding, and scaling is frequently tested.
- Model Deployment Concepts — Many overlook UDFs, external functions, and registry details.
- GenAI and LLM Integration — Since Snowflake Cortex is newer, candidates sometimes skip preparing for embedding and fine-tuning workflows.
The best approach is to balance your study across all four domains while gaining hands-on practice with Snowpark and Snowflake ML APIs.
How long does the SnowPro Advanced Data Scientist certification remain valid?
This certification remains valid for 2 years from the date of issue.
To renew, you can either:
- Earn another eligible SnowPro Advanced certification.
- Take approved Snowflake Instructor-Led Training (ILT) courses.
- Recertify through Snowflake’s Continuing Education program.
This ensures credential holders are always aligned with Snowflake’s evolving capabilities.
How can I prepare effectively for the DSA-C03 Snowflake certification?
A structured preparation plan is key. Recommendations include:
- Instructor-led Data Science Training from Snowflake
- Self-study using Snowflake documentation and technical blogs
- Hands-on labs and experiments with machine learning inside Snowflake
- Reviewing statistical concepts and ML lifecycle best practices
To boost your confidence, we highly recommend using SnowPro Advanced Data Scientist practice exams with full explanations. These mock tests simulate the real exam experience and help you strengthen weak areas before taking the official exam.
How does this certification fit into a long-term career path?
This certification doesn’t just validate Snowflake skills; it positions you as a forward-thinking data scientist capable of driving enterprise AI transformation.
It can complement or precede other advanced SnowPro certifications such as Data Engineer, Architect, or Administrator, giving you an elite specialization that matches your career goals.
What special Snowflake capabilities are emphasized on the exam?
This certification highlights modern and in-demand data science approaches:
- Snowpark APIs for Python, SQL, and Scala
- Feature Store for scalable ML feature management
- Cortex GenAI framework for embeddings, prompts, and fine-tuning
- Snowflake Model Registry for governance, versioning, and monitoring
- Deployment via UDFs, external functions, and containerized services
By mastering these, you become proficient in running full ML and AI workflows directly on Snowflake’s AI Data Cloud.
How do I register for the Snowflake SnowPro Advanced Data Scientist Certification exam?
It’s simple to register and begin your certification journey:
- Visit the official Snowflake SnowPro Advanced Data Scientist Certification page.
- Select “Register Now” and log into the Certification Management system.
- Pick your preferred test method (online or in-person).
- Choose a date, complete your registration, and get ready to excel!
The Snowflake SnowPro Advanced Data Scientist Certification is a fantastic way to display your mastery of AI, ML, and data science capabilities in the Snowflake ecosystem. Earning this credential demonstrates not only your advanced technical expertise but also your ability to thrive in the future of enterprise AI and analytics. With steady preparation, hands-on labs, and structured study guides, you’ll be ready to pass the exam and accelerate your career to new heights.
