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Data Scientist Curriculum

Data Scientist Curriculum

Focus on extracting value from industrial data through advanced analytics, visualization, and efficient data retrieval in Cognite Data Fusion.

Level 1

Foundation

Essential knowledge required for all subsequent courses.

Learning Path Foundation

Cognite Data Fusion Fundamentals with Data Modeling

Master the core concepts of data ingestion, contextualization, and the foundational architecture. This comprehensive path sets the stage for advanced engineering tasks.

Start Path
6 Hours
Level 2

Core Data Scientist Skills

Master the tools and techniques for analyzing industrial data.

Core Transformation

Data Transformation

Utilize CDF Transformations to convert data from the RAW layer into the Core Data Model.

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Core Modeling

Data Modeling

Structure and manage data using containers, views, and semantic layer best practices.

Coming Soon
Core Context

Contextualization

Understand the concept of asset hierarchy and perform basic linking of CogniteTimeSeries and files to CogniteAssets.

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Core SDKs

Tooling

Demonstrate basic proficiency with the Cognite Python SDK and Toolkit for simple read/write operations and authentication.

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Core Governance

Governance

Properly define and apply Spaces to manage data ownership and access control.

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Core Analytics

Visualization and Exploration

Learn to utilize Cognite Charts, Canvas, and third-party integrations to visualize and explore industrial data.

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Core Querying

Efficient Data Retrieval

Master advanced filtering and retrieval patterns to access large-scale industrial data efficiently via SDKs.

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Level 3

Specialization & Advanced Topics

Deep dive into specific capabilities once you have the core skills.

Level 3 Coming Soon

Advanced specialization tracks for Data Scientists, including Industrial AI, Function Scheduling, and Advanced Analytics, are currently under development.

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