Technologies / Data & Analytics

Jupyter for Data Science Teams

A one-day practical training dedicated to effective use of Jupyter Notebooks in Data Science teams. The program focuses on best practices for collaboration, code organization, and managing analytical projects. Participants will learn advanced Jupyter Lab features and tools supporting teamwork. The training is conducted in workshop format with emphasis on practical application of learned techniques in real project environments.

Why choose this training?

Modern organizations increasingly need specialists, technical competencies have become a critical asset. A one-day practical training dedicated to effective use of Jupyter Notebooks in Data Science teams. The program focuses on best practices for collaboration, code organization, and managing analytical projects.

Upon completion, participants will be able to: Ability to work effectively in DS teams, Knowledge of best practices for project organization, Ability to manage complex analytical projects, Knowledge of process automation in Jupyter. These competencies directly translate into higher effectiveness in IT projects.

This training is particularly valuable for: Data analysts working in teams, Data Scientists, Data engineers.

What makes our approach unique?

The EITT approach is based on hands-on experience and practical exercises. Over 1 day of intensive training, participants work on real-world examples and scenarios, ensuring not only theoretical understanding but practical application skills.

With over 2,500 trainings in our portfolio and a 4.8/5 participant rating, EITT is a trusted partner in IT competency development for organizations of all sizes. Our trainers are experienced practitioners who share up-to-date knowledge and proven solutions.

Looking for training tailored to your team’s needs? Contact us — we’ll prepare a program customized to your requirements.

Benefits

Ability to work effectively in DS teams
Knowledge of best practices for project organization
Ability to manage complex analytical projects
Knowledge of process automation in Jupyter
Ability to collaborate in version control systems
Practical experience in code documentation
Knowledge of tools supporting teamwork

Who is this training for?

Data analysts working in teams

Data Scientists

Data engineers

Analytical team leaders

Researchers collaborating on projects

Python programmers in DS teams

ML specialists working with Jupyter

Prerequisites

Basic knowledge of Jupyter Notebooks
Experience in Python programming
Knowledge of data analysis fundamentals
Basics of working with version control systems

Training program

Advanced editor features
Integration with version control systems

Project Organization
Analytical project structure
Dependency management
Notebook documentation

Team Collaboration
Best practices for group work

Code review in notebooks

Automation and Deployments
Converting notebooks to scripts
Scheduling notebook execution

Sharing results

Delivery Methods

Online

Convenience of participating from anywhere
Interactive live sessions with trainer
Materials available for 30 days
No travel costs

On-site

Direct contact with trainer and group
Intensive hands-on workshops
Networking with other participants
Full focus on learning

Training Topics

Frequently asked questions

What are the prerequisites for this training?

For Jupyter for Data Science Teams we recommend: Basic knowledge of Jupyter Notebooks; Experience in Python programming; Knowledge of data analysis fundamentals.

What is the format and duration of this training?

The training lasts 1 day and is available in online and on-site format. Sessions run from 9:00 AM to 4:00 PM. We can also customize the schedule to fit your team's needs.

Who is this training designed for?

This training is designed for: Data analysts working in teams; Data Scientists; Data engineers.