701-3001-00L Environmental Systems Data Science: Data Processing
| Semester | Spring Semester 2023 |
| Lecturers | L. Pellissier, E. J. Harris, J. Payne |
| Periodicity | yearly recurring course |
| Course | Does not take place this semester. |
| Language of instruction | English |
Courses
| Number | Title | Hours | Lecturers | |
|---|---|---|---|---|
| 701-3001-00 G | Environmental Systems Data Science: Data Processing Does not take place this semester. Lecture: Di 13-14 Exercises: Di 14-16 | 1.5 hrs | L. Pellissier, E. J. Harris, J. Payne |
Catalogue data
| Abstract | Students are introduced to a typical data science workflow using various examples from environmental systems. They learn common methods and key aspects for each step through practical application. The course enables students to plan their own data science project in their specialization and to acquire more domain-specific methods independently or in further courses. |
| Learning objective | The students are able to ● frame a data science problem and build a hypothesis ● describe the steps of a typical data science project workflow ● conduct selected steps of a workflow on specifically prepared datasets, with a focus on choosing, fitting and evaluating appropriate algorithms and models ● critically think about the limits and implications of a method ● visualise data and results throughout the workflow ● access online resources to keep up with the latest data science methodology and deepen their understanding |
| Content | ● The data science workflow ● Access and handle (large) datasets ● Prepare and clean data ● Analysis: data exploratory steps ● Analysis: machine learning and computational methods ● Evaluate results and analyse uncertainty ● Visualisation and communication |
| Prerequisites / Notice | 252-0840-02L Anwendungsnahes Programmieren mit Python 401-0624-00L Mathematik IV: Statistik 401-6215-00L Using R for Data Analysis and Graphics (Part I) 401-6217-00L Using R for Data Analysis and Graphics (Part II) 701-0105-00L Mathematik VI: Angewandte Statistik für Umweltnaturwissenschaften |
Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 3 credits |
| Examiners | L. Pellissier, E. J. Harris, J. Payne, M. Volpi |
| Type | ungraded semester performance |
| Language of examination | English |
| Repetition | Repetition only possible after re-enrolling for the course unit. |
Learning materials
| No public learning materials available. | |
| Only public learning materials are listed. |
Groups
| No information on groups available. |
Restrictions
| Places | 80 at the most |
| Priority | Registration for the course unit is until 24.02.2023 only possible for the primary target group |
| Primary target group | Environmental Sciences BSc (727000) starting semester 06 |
| Waiting list | until 03.03.2023 |
Offered in
| Programme | Section | Type | |
|---|---|---|---|
| Environmental Sciences Bachelor | Methodes of Statistical Data Analysis | W |  |