Prototyping data science products HS25
(Fall semester, Seminar)
Objective:
The main objective is to teach students how to transform their ideas and data science knowledge into a product prototype. During the seminar, the students will improve their programming skills in R or Python (at their choice), learn to apply machine learning techniques to a concrete problem, create a product prototype and run it on the cloud. All participants will receive free credits on the Google Cloud Platform (courtesy of a Google Educational Grant) that they can use to get familiar with the services and cover the cost of running their product prototype.
Learning outcome:
The seminar gives an overview of the fundamental steps needed to create a product prototype for a data science web application. Topics include getting familiar with google cloud computing platform, training machine learning algorithms, structuring a project and running it on the cloud. Most services we discuss provide a high-level, user friendly (often graphical) interface. Therefore, no previous knowledge of cloud infrastructure is required.
Syllabus: forthcoming
Instructors:
Dr. Radu Tanase
Mingmin Feng
Contact:
Radu.tanase@business.uzh.ch
Type:
Seminar
Target audience:
MA students with basic programming and machine learning knowledge, who are interested in turning their ideas into a web application. Assigned to “Wahlpflichtbereich BWL 4”.
Frequency:
Each Fall Semester
AP(ECTS)-points:
6
Language: English
Course material:
Slides, videos, and other learning resources will be provided during the seminar
Prerequisites:
Students can choose to program in either R or Python. Therefore, we recommend the following courses:
A non-technical introduction to R (or equivalent knowledge)
OR
A non-technical introduction to Python (or equivalent knowledge).
Recommended prior knowledge:
Good programming knowledge in R or Python. Basic knowledge of machine learning.
Grading:
The grade is comprised of 5 main components:
1. Online exercises: 10%
2. Minimal product: 25% (50% group outcome; 50% individual grade)
3. Advanced product: 25% (50% group outcome; 50% individual grade)
4. Group Project: 30%, final presentations on 11.12.2025
5. Peer evaluation: 10%
Dates and Location:
Thursdays
18.09.2025 |
14:00 - 18:00 (KO2-D-54) |
25.09.2025 |
14:00 - 18:00 (KO2-D-54) |
16.10.2025 |
14:00 - 18:00 (KO2-D-54) |
30.10.2025 |
14:00 - 18:00 (KO2-D-54) |
27.11.2025 |
14:00 - 18:00 (KOL-G-210) |
11.12.2025 |
14:00 - 18:00 (KOL-G-210) |
Registration:
The number of participants is limited to 12. To apply, please send your application via email to mingmin.feng@business.uzh.ch with the subject "Application PDSP HS2025". The application should contain your CV, transcript of records, and a short letter of motivation. The application deadline is Wednesday, September 10, 2025, at 23:59 CEST. The application results will be communicated on Friday, September 12. Please note that students who have taken a previous variant of this course are not eligible to take the seminar again.
Note:
This information supports the official information in the electronic university calendar (VVZ – Vorlesungsverzeichnis). In case of doubt, the official information at the VVZ is valid.
Data Camp
This class is supported by DataCamp, the most intuitive learning platform for data science and analytics. Learn any time, anywhere and become an expert in R, Python, SQL, and more. DataCamp’s learn-by-doing methodology combines short expert videos and hands-on-the-keyboard exercises to help learners retain knowledge. DataCamp offers 325+ courses by expert instructors on topics such as importing data, data visualization, and machine learning.
