Snowflake + Python (Snowpark)

Module 1: Introduction to Snowpark and Snowflake

• Snowflake overview and Snowpark architecture
• Setting up Snowpark Python environment

Module 2: Data Processing with Snowpark DataFrames

• Loading, transforming, and manipulating data
• Applying Python functions on data

Module 3: Creating and Managing User-Defined Functions (UDFs)

• Writing Python UDFs and UDTFs
• Best practices in function management

Module 4: Developing Stored Procedures Using Python

• Automating business logic with Python stored procedures

Module 5: Machine Learning with Snowpark ML

• Training, evaluating, and deploying ML models
• Using Snowflake for ML workloads

Module 6: Integration with Python Ecosystem

• Using libraries like Pandas, Scikit-learn with Snowpark
• Vectorized UDF deployment for performance

Module 7: Performance Optimization and Monitoring

• Optimizing Snowpark Python code
• Debugging and monitoring applications

Module 8: Security and Compliance

• Data security practices in Snowpark development

Module 9: Hands-on Labs and Real-world Use Cases

• Building end-to-end pipelines and ML workflows

Module 10: Certification Preparation

• Exam strategies and sample questions

Experience in the Industry Gain knowledge from experts with practical Snowflake + Python (Snowpark) project experience in a variety of sectors.

Backgrounds at the Top Prominent corporations such as hcl, tcs , accenture  and cognizant  employ trainers.

Clear & Effective Teaching Excellent communication and real-world examples simplify complex subjects.

Hands-On Learning Focus Students can apply their abilities in real-world situations with the use of case studies and real-time projects.

Up-to-Date Knowledge Trainers stay current with the latest tools, techniques and best practices.