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.
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:
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, Giuseppe Casalicchio, Christoph Molnar
- Time: Friday, 2 - 6 pm c.t., starting in the winter semester 2017/2018
- ECTS: 12 ECTS (e.g. as an alternative to the Statistical Consulting or Data Science Practical)
Eligibility Requirements
- Good knowledge in R, e.g. "Programming with statistical Software (R)" or better: "Advanced Programming with R"
- Predictive Modelling, FCIM or Machine Learning
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:- Part 1 (Lecture): Teaches fundamental topics in software engineering and project management in an inverted classroom style (with demos, discussions and hands-on exercises).
- Part 2 (Issue solving): You are expected to help to solve some issues/bugs in existing libraries.
- Part 3 (Project): Students team up in groups of 3-4 persons and implement a project of their choice
- Trainer/in: Bernd Bischl
- Trainer/in: Giuseppe Casalicchio
- Trainer/in: Jann Goschenhofer
- Trainer/in: Christoph Molnar