Introduction to Cognite Python SDK

Collect data with the Cognite Python SDK.

rate limit

Code not recognized.

About this course

Welcome to Introduction to Cognite Python SDK!
You will explore Cognite Python SDK by using a Google Colab notebook. First, you will look at the purpose of the Python SDK. Then, the course will walk you through the setup of the Google Colab notebook. You will learn how to use it, by simply listing data from Cognite Data Fusion. Also, the course takes you through current use cases in data science and how to create models with Cognite Python SDK. In the end, there will be a puzzle where you will use the gained knowledge to solve it.  For this course, you will connect to Open Industrial Data: live data from the Valhall Oil Rig in the North Sea.

 

After the course, you will be able to:

  • Search for assets.
  • List events.
  • Understand the asset hierarchy.
  • Collect time series data.
  • Visualize time series plots.
 

Who should take this course?
Data engineers, data scientists, and anyone interested in using the Cognite Python SDK.

Instructor
Cognite Academy has developed this course with: 

Sunil Krishnamoorthy
Product Manager

 

Rebecca Seyfarth
Senior ML Engineer

Knowledge prerequisites
Basic knowledge of Python.

Technical prerequisites
You will be working with real industrial data from the Open Industrial Data project. 
For the hands-on part, the course material is in Google Colab. If you'd like to work in Google Colab, you must be using either Chrome (preferred), Firefox, or Safari. If you would prefer to run code cells outside of Google Colab, you can download the notebook or copy the code directly from the course.
In this course, you will be alternating between two windows: this e-learning course and Google Colab. Therefore we suggest using two screens if possible to make switching windows easier.

Content1 hr 30 min

  • Introduction
  • Access and setup
  • Access the CDF project
  • Google Colab setup
  • Environment setup
  • Data collection
  • Retrieving lists of assets
  • Check your knowledge
  • Events
  • Check your knowledge
  • Asset hierarchy and relationships
  • Check your knowledge
  • Collecting time series data
  • Use cases of CDF data
  • Check your knowledge
  • Data model
  • Data Science section (Optional)
  • Data science in asset-heavy industries
  • Current use cases
  • Model creation
  • Linear regression model
  • Random forest ensemble model
  • Puzzle
  • The puzzle
  • Hints
  • Check your knowledge
  • Puzzle solutions
  • Share your feedback
  • End of course

About this course

Welcome to Introduction to Cognite Python SDK!
You will explore Cognite Python SDK by using a Google Colab notebook. First, you will look at the purpose of the Python SDK. Then, the course will walk you through the setup of the Google Colab notebook. You will learn how to use it, by simply listing data from Cognite Data Fusion. Also, the course takes you through current use cases in data science and how to create models with Cognite Python SDK. In the end, there will be a puzzle where you will use the gained knowledge to solve it.  For this course, you will connect to Open Industrial Data: live data from the Valhall Oil Rig in the North Sea.

 

After the course, you will be able to:

  • Search for assets.
  • List events.
  • Understand the asset hierarchy.
  • Collect time series data.
  • Visualize time series plots.
 

Who should take this course?
Data engineers, data scientists, and anyone interested in using the Cognite Python SDK.

Instructor
Cognite Academy has developed this course with: 

Sunil Krishnamoorthy
Product Manager

 

Rebecca Seyfarth
Senior ML Engineer

Knowledge prerequisites
Basic knowledge of Python.

Technical prerequisites
You will be working with real industrial data from the Open Industrial Data project. 
For the hands-on part, the course material is in Google Colab. If you'd like to work in Google Colab, you must be using either Chrome (preferred), Firefox, or Safari. If you would prefer to run code cells outside of Google Colab, you can download the notebook or copy the code directly from the course.
In this course, you will be alternating between two windows: this e-learning course and Google Colab. Therefore we suggest using two screens if possible to make switching windows easier.

Content1 hr 30 min

  • Introduction
  • Access and setup
  • Access the CDF project
  • Google Colab setup
  • Environment setup
  • Data collection
  • Retrieving lists of assets
  • Check your knowledge
  • Events
  • Check your knowledge
  • Asset hierarchy and relationships
  • Check your knowledge
  • Collecting time series data
  • Use cases of CDF data
  • Check your knowledge
  • Data model
  • Data Science section (Optional)
  • Data science in asset-heavy industries
  • Current use cases
  • Model creation
  • Linear regression model
  • Random forest ensemble model
  • Puzzle
  • The puzzle
  • Hints
  • Check your knowledge
  • Puzzle solutions
  • Share your feedback
  • End of course