This three-day course for Architects and Technical Leaders provides the skills, knowledge, and Snowflake recommended best practices to deploy and operate Snowflake, insights and recommendations based upon real-world customer experiences, and the confidence to get the most out of Snowflake’s technology.
Advance your Snowflake AI Data Cloud skills with Trainocate’s certification training.
Expert instructors and practical labs help you master data engineering, analytics, and AI workflows so you can use Snowflake’s platform with confidence and drive real impact.
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This two-day, role-specific course introduces data analysts to how the Snowflake AI Data Cloud enables them to deliver actionable insights and reports to their organization to drive business value. The course is structured around a data analysis lifecycle placing each capability Snowflake provides in the data analyst’s context. The course begins with how to connect to the Snowflake Data Cloud. It then covers how to analyze, ingest, enrich, report, and diagnose data insights with Snowflake. The course consists of lectures, labs, demonstrations, and discussions.
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This three-day, role-specific course provides an in-depth exploration of database administrator duties and responsibilities in the Snowflake AI Data Cloud. This course covers data loading performance, security, role hierarchy design, and performance tuning. The course consists of lectures, labs, demonstrations, and discussions.
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This two-day, role-specific course presents additional topics and a deep dive into select subjects for the Data Engineer through the lens of the data engineering lifecycle. The course covers Snowflake concepts, features, considerations, and best practices intended for stakeholders who will be accessing, developing, and querying datasets for analytic tasks, and building data pipelines in Snowflake. This course consists of data engineering concepts delivered through lectures, demos, labs, and discussions.
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This four-day course covers the core concepts, design considerations, and Snowflake recommended best practices intended for critical stakeholders who will be working on the Snowflake AI Data Cloud. The course consists of lectures, demos, and labs covering a wide range of essential topics.
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This three-day role-specific course covers key concepts, features, considerations, and Snowflake recommended best practices through the lens of the data engineering workflow. It is intended for participants who will be accessing, developing, and querying datasets for analytic tasks and building data pipelines in Snowflake. This course consists of core data engineering concepts delivered through lectures, demos, labs, and discussions.
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This three-day, role-specific course is intended for participants interested in developing skills and experience using Snowflake AI Data Cloud for data science workloads. The participant will gain exposure to the rich features of Snowflake, diverse machine learning datasets, relevant and popular open source ML frameworks and libraries, and model deployment practices that will provide practical skills applicable to data science jobs. This course consists of lectures, demos, labs, and discussions.
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In this two-day course, participants will learn how to seamlessly integrate cutting-edge AI capabilities into their daily work, even if they’re not data scientists or Machine Learning engineers. They will extract insights at scale, interact with applications using natural language, drive coding productivity, and produce new content. Participants will also learn about empowering business users to make faster, data-driven decisions while enabling data teams and developers to build and deploy specialized, governed AI agents rapidly.
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This one-day, role-specific course introduces business users to the Snowflake AI Data Cloud and its architecture. Participants learn how to connect to Snowflake, access the data they need, use that data, augment the data, and report data insights from Snowflake. The course consists of lectures, labs, demonstrations, and discussions.
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In this course you will learn how to translate various concepts in Snowflake to the analogous concepts in BigQuery. You will learn how the high-level architectures of Snowflake and BigQuery compare, understand differences in how to configure datasets and tables, map data types in Snowflake to data types in BigQuery, understand schema mapping from Snowflake to BigQuery, optimize your new schemas in BigQuery, and do a high-level comparison of SQL dialects in Snowflake and BigQuery.
