Cursor for Data Science

​Learn how data science teams use Cursor to accelerate analytics workflows, from exploratory analysis to production pipelines.

​We'll cover:

• ​Native notebook support: Work with Jupyter notebooks and Python scripts with full AI assistance. Use Tab, Inline Edit, and Agents to use pandas, NumPy, scikit-learn, and data visualization libraries.

• ​MCP integrations and database connectivity: Connect directly to Databricks, Postgres, BigQuery, Snowflake, and other databases using MCP servers.

• ​SQL generation and data querying: Generate optimized SQL statements, execute queries against your databases, and analyze results directly in the IDE

​Perfect for data scientists, analysts, and ML engineers looking to accelerate their common data workflows.

​​The session will be recorded and shared with all registered participants.