Einschreibeoptionen

Use the registration key (Einschreibeschlüssel) "bigDS" to read more about the course.
This course aims to foster the practice of software engineering and project management techniques in R within the context of data science and machine learning projects. 

Organization

  • Lecturers: Bernd Bischl, Christoph Molnar Florian Pfisterer
  • Time: Thursday, 9 - 12 pm s.t. Attention: The lecture only takes place for the first 4 weeks of the semester (18.10. - 15.11.). Later on, during the project phase, only regular meetings with the lecturers are required.
  • Place: Edmund Rumpler Str. 13 - Room B 247 (Freimann)
  • ECTS: 12 ECTS (e.g. as an alternative to the Statistical Consulting or Data Science Practical)

Eligibility Requirements

  • Good programming skills in Data science related languages (R, Python, Julia, C++, etc.)
  • Predictive Modelling, FCIM or comparable Machine Learning courses

Projects

  • Industry Projects with several Munich-based industry leaders
  • Research / Data Science for Social Good projects 

General Course Setup

The course starts with a kick-off meeting and is divided into three major parts with a weekly meeting during the semester:

  1. Part 1 (Lecture): Teaches fundamental topics in software engineering and project management in an inverted classroom style (with demos, discussions and hands-on exercises). This part takes place from 18.10. - 15.11. on Thursday mornings. At the end of the lecture phase, students will be able to choose a group project they want to work on during the semester. Own proposals are welcome but need to be submitted in the first two weeks of the semester. 
  2. Part 2 (Project): Students team up in groups of 2-5 persons and implement a project of their choice. Project descriptions will be made available at the beginning of November. In this phase, attendance is only required for regular meetings with project partners and supervisors.



Part 1 - Lecture: Contents

18.10. Introduction & Course Structure

25.10. - 15.11. :

- Introduction to R, R Package Development and Documentation

- Git and Gitlab

- Unit Testing and Continuous Integration

- Project Assignments



Selbsteinschreibung (Teilnehmer/in)