Data Science Week
- Veranstaltungsformat:
- Präsenzveranstaltung
- Veranstaltungsort:
-
- Bootshaus Universität Kassel
- Veranstalter:
-
- Graduiertenakademie
- Kategorie:
-
- Workshop
- Zielgruppe:
-
- Promovierende/Doktorand:innen
Language: English.
Are you working on your PhD project and ready to dive into data analysis? Whether you’ve just collected your first datasets or are preparing the final figures for your thesis or a peer-reviewed journal, this course is tailored for you. Learn efficient and elegant data analysis strategies, create impactful visualizations, and accelerate the progress of your research.
Course Goals
Participants will:
- Gain a solid foundation in Python-based data analysis methods.
- Practice effective data analysis and visualization strategies
- Learn proactive and independent self-learning habits beyond the bootcamp week
- Apply new techniques directly to their own research projects, ensuring seamless integration of skills into their work.
Course Structure
The week is divided into two components:
1. Interactive Learning Sessions (50%): Participants will engage with key data analysis topics through interactive Python notebooks. These serve as both teaching tools and resources for future work.
2. Project Work & Coaching (50%): Participants dedicate time to their own projects with access to one-on-one coaching sessions from the trainer, Dr. Alexander Britz.
Contents
- Numpy
- Matplotlib & Seaborn
- File Handling & Coding Practices
- AI Coding Tools
- Pandas & Scipy
- Intorduction to Machine Learning
Prerequisites
A basic understanding of Python is required. For those needing a refresher, we offer an optional online pre-course, “Python Kickstart".
Preliminary Agenda
| Time | Monday | Tuesday | Wednesday | Thursday | Friday |
| 9-9:15 | Check-in and Q&A | ||||
| 9:15-10:45 | Introduction round with discussion about projects for the week | Input: Reading and Writing of Files, Coding with AI Tools
| Input: Analysis of large tabular datasets with Pandas
| Input: Regression and classification with Scikit-Learn
| Input: Neural networks with Pytorch
|
| 10:45-11:00 | Coffee Break | ||||
| 11:00-12:30 | Input: NumPy for data handling | Project Work & Individual Coaching | Project Work & Individual Coaching | Project Work & Individual Coaching | Project Work & Individual Coaching |
| 12:30-13:30 | Lunch Break | ||||
| 13:30-15:00 | Input: Visualizations with Matplotlib and Seaborn | External Guest: Research Data Service: Data and Software Management | Input: SciPy for curve fits, filtering, and Interpolation | Input: Good Coding Practice with Git and virtual environments, Coding with AI Tools | Project Work & Individual Coaching |
| 15:00-15:15 | Coffee Break | ||||
| 15:15-16:45 | Project Work & Individual Coaching | Project Work & Individual Coaching | Project Work & Individual Coaching | Project Work & Individual Coaching | Short presentation = elevator pitch (3-5 min each participant) of what has been achieved in one week! |
| 16:45-17:00 | Q&A and checkout | ||||
Weitere Informationen zu dieser Veranstaltung
Veranstaltungsort:
Bootshaus Universität Kassel
Auedamm 27a
34121 Kassel
Auf Karte anzeigen
Veranstalter:
Graduiertenakademie
Kontaktperson:
Gianna Dalfuß
Universität Kassel
Graduiertenakademie
Koordination der überfachlichen Promovierendenausbildung | Kasseler Graduiertenprogramm
0561 804 2427
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Trainer:
Dr. Alexander Britz
Dr. Alexander Britz holds a PhD in physics from the Universität Hamburg. With over a decade of experience in Python and MATLAB for interdisciplinary research—including postdoctoral work at Stanford University—Dr. Britz combines technical expertise with his skills as a trainer, coach, and lecturer in data analysis and communication.