R, Python and Julia: | |
Course Leader | Christian Kauth |
Target Group | Statistical production units and methodologists of NSIs, having an interest in data science tools and a basic understanding of development. |
Entry Qualifications | Sound command of English. Participants should be able to make short interventions and to actively participate in discussions |
Objective(s) | This course will enable you to pick your next top data-science programming language
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Contents | The scope of the course is to have a general overview of the languages and to show main advantages. The course should cover: Installing/where to find the software (resources, etc) Installing modules/libraries Basic programming Fetching data from Eurostat API Basic data analysis and visualization tools Ideally, the same use case could be done in the different languages. |
Expected Outcome | It is not expected that the audience will learn to develop with Python, R, and Julia at the end of the course but have a global idea about the technologies and understand the main differences. |
Training Methods | The course is split in 3 modules of 2h each, each one focusing on a different technology for data science: Python, R and Julia. |
Required Reading | None |
Suggested Reading | None |
Required Preparation |
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Trainer(s)/ Lecturer(s) | Christian Kauth (Independent expert) |
Practical Information | ||||
When | Duration | Where | Organiser | Application via National Contact Point |
24, 26, 28.02.2025 (14h – 16h) | 3 sessions, 2h each | ONLINE | ICON-INSTITUT Public Sector GmbH | Deadline: 06.01.2025 |