Snowflake for Machine Learning Training

Live Online & Classroom Enterprise Training

Learn how to leverage Snowflake’s powerful data cloud platform for Machine Learning workflows, including data preparation, model training, and deployment at scale.

Looking for a private batch ?

REQUEST A CALLBACK

Enterprise Reporting
Lifetime Access
CloudLabs
24x7 Support
Real-time code analysis and feedback

What is Snowflake for Machine Learning Course about?

The Snowflake for ML course introduces learners to using Snowflake’s cloud data platform as a foundation for modern Machine Learning (ML) and AI solutions. The course covers how to prepare and manage large datasets, integrate with ML frameworks like Python, TensorFlow, or Snowpark ML, and operationalize models directly within Snowflake. Participants will explore end-to-end ML pipelines, including data ingestion, feature engineering, training, and model deployment, using Snowflake’s built-in compute and secure collaboration capabilities.

What are the objectives of Snowflake for Machine Learning Course ?

Understand Snowflake’s architecture and capabilities for ML workloads.
Use Snowpark and Python to build and deploy ML models within Snowflake.
Perform feature engineering and large-scale data preparation efficiently.
Integrate Snowflake with external ML frameworks and cloud services.
Implement scalable and secure ML pipelines for production environments.

Who is Snowflake for Machine Learning Course for?

Data Scientists and Machine Learning Engineers.
Data Engineers managing large-scale data pipelines.
AI Developers integrating ML with cloud data platforms.
BI Analysts exploring predictive analytics in Snowflake.
Technical professionals seeking to bridge data and ML workflows.

What are the prerequisites for Snowflake for Machine Learning Course?

Prerequisites:

Basic understanding of Machine Learning concepts.
Working knowledge of SQL and Python.
Familiarity with Snowflake fundamentals or cloud data warehouses.
Understanding of data modeling and ETL concepts.
Access to a Snowflake environment for hands-on practice.

Learning Path:

Introduction to Snowflake for Machine Learning
Data Preparation and Feature Engineering using Snowpark
Integrating Snowflake with ML Frameworks (e.g., TensorFlow, scikit-learn)
Model Deployment and Inference within Snowflake
MLOps and Performance Optimization in Snowflake

Related Courses:

Snowflake – Masterclass
Data Engineering with Snowflake
Machine Learning with Python
MLOps on Azure / AWS

Available Training Modes

Live Online Training

4 Days

Course Outline Expand All

Expand All

Module 1: Introduction to Snowflake

Overview of Snowflake’s architecture and features

Benefits of using Snowflake for ML projects

Understanding Snowflake’s data sharing and scalability

Module 2: Snowflake for Data Preparation

Loading and managing data in Snowflake

Querying and transforming data with SQL

Best practices for feature engineering in Snowflake

Hands-on Lab: Preparing data for ML models

Module 3: Integrating Snowflake with ML Tools

Connecting Snowflake with Python and Jupyter Notebooks

Using Snowflake’s Python connector and Snowpark

Data extraction and transformation for ML pipelines

Hands-on Lab: Setting up a Snowflake-powered ML environment

Module 4: ML Model Development and Deployment

Training ML models using Snowflake-stored data

Deploying models using Snowflake and external ML frameworks

Real-time predictions with Snowflake integrations

Hands-on Lab: Training and deploying an ML model using Snowflake

Module 5: Advanced Features and Optimization

Performance tuning for large-scale ML applications

Using Snowflake’s UDFs (User Defined Functions) for ML tasks

Advanced analytics with Snowflake’s data pipelines

Hands-on Lab: Optimizing ML workflows in Snowflake

Module 6: Security and Governance for ML Workflows

Data privacy and compliance in Snowflake

Implementing role-based access control (RBAC)

Audit trails and monitoring for ML workflows

Best practices for secure ML pipelines

Module 7: Real-World Use Cases

Case studies of ML projects powered by Snowflake

Industry-specific applications (e.g., finance, healthcare, retail)

Group exercise: Designing an end-to-end ML workflow with Snowflake

Who is the instructor for this training?

The trainer for this Snowflake for Machine Learning Training has extensive experience in this domain, including years of experience training & mentoring professionals.

Reviews

My outlook on training changed completely after attending SpringPeople BPC training. The content, the trainer and infrastructure at SpringPeople were top notch and perfectly in tune with the industry requirements. Regardless to say, training is now something that I look forward to to. Kudos to everyone at SpringPeople!

Shweta Priya

Sony

I attended the 3-day AngularJs training at SpringPeople. The trainer was an industry veteran with vast experience in the subject. Notably, the hands-on training, and the Q&A session stood out. Overall, I found SpringPeople a great place to learn with excellent facilities and great trainers. Would recommend SpringPeople to my colleagues and friends.

Swati Singh

I attended the training on API Design for Mulesoft. The sessions were well planned and value-laden. I benefited immensely from the hands-on experience enabled through virtual labs. I would like to specifically commend the efficiency of the support team who were always available to resolve my concerns.

Nikhil Kohli

Stryker

I attended the jQuery training batch, conducted by Mr. Vijay, an SME who did a thorough coverage of all the essentials. He took us through concepts such as jQuery animations, event handlers, plugins, and jQuery-UI by small programs, very easily. The sessions were useful and well structured. By the end of the training, I was well equipped to develop a SPA on Product Management System. Overall, the learning experience at SpringPeople was great!

Heena Rajan

Mindtree