greenchoice

Data Science as the next step in data maturity - Greenchoice

Greenchoice has already taken considerable steps with an ambitious data strategy, future-proof data architecture and a rapidly growing number of end users in the data visualisation environment. However, in order to take the next step in data maturity, Greenchoice has developed an in-company Data Science training in collaboration with Rockfeather. The training's main objectives were: identify, develop, and implement Data Science use cases. Alex Janssen, Manager Development Consumer and Data & Analytics explains what this training has brought while also answering the question: When is the Data Science training relevant for you?

“The Data Science training is the best solution for you when you hear that Data Science is the next step in data maturity from both your employees, as well as, from the board!”

– Alex Janssen, Manager Development Consument en Data & Analytics

The next step in data maturity?

Greenchoice has made considerable progress in the area of data maturity. In recent years, the company has:

  • Outlined an ambitious data strategy;
  • Implemented a future-proof and scalable data architecture;
  • Rolled out a dynamic data visualisation environment for a rapidly growing number of end users.

The board and staff of Greenchoice’s data team agree: Data Science is the next step in data maturity. To take this step successfully, Greenchoice has developed an in-company Data Science training in collaboration with Rockfeather, fully tailored to the needs and wishes of the Data & Analytics, and Trading & Forecasting teams. The main goal of this training? To successfully identify, develop, and implement Data Science use cases within Greenchoice.

The contents of the training

In order to achieve this goal, a special program in collaboration with local partners Erasmus Universiteit Rotterdam, UbiOps, and The Commercials Works was created:

  • Data Science – Python training; 
    • Python introduction + environment set-up 
    • List for loops, functions, and scope 
    • Milestone project | scrape a website 
    • Classes and Object-Oriented-Programming 
    • Project structure
  • Data Science models and techniques; 
    • AI/ML introduction 
    • Classification  
    • Regression
    • Clustering
  • Pet projects 
    • Churn 
    • Customer segmentation
    • Practical Time Series Analysis & Forecasting 
  • Analytics Translation Training 
    • Machine Learning Canvas 
    • Agile Scrum for data science projects 
    • DevOps / MLOps 

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