7 hours (usually 1 day including breaks)
- Programming experience in languages such as Python, R, Scala, etc.
- A background in data science
Jupyter is an open-source, web-based interactive IDE and computing environment.
This instructor-led, live training introduces the idea of collaborative development in data science and demonstrates how to use Jupyter to track and participate as a team in the "life cycle of a computational idea". It walks participants through the creation of a sample data science project based on top of the Jupyter ecosystem.
By the end of this training, participants will be able to:
- Install and configure Jupyter, including the creation and integration of a team repository on Git
- Use Jupyter features such as extensions, interactive widgets, multiuser mode and more to enable project collaboraton
- Create, share and organize Jupyter Notebooks with team members
- Choose from Scala, Python, R, to write and execute code against big data systems such as Apache Spark, all through the Jupyter interface
- Data science teams
Format of the course
- Part lecture, part discussion, exercises and heavy hands-on practice
- The Jupypter Notebook supports over 40 languages including R, Python, Scala, Julia, etc. To customize this course to your language(s) of choice, please contact us to arrange.
To request a customized course outline for this training, please contact us.
It is great to have the course custom made to the key areas that I have highlighted in the pre-course questionnaire. This really helps to address the questions that I have with the subject matter and to align with my learning goals.
Winnie Chan - Statistics Canada