(Fall semester, Seminar)
The seminar gives an overview of the fundamental steps needed to create a product prototype for a data science application. Topics include getting familiar with google cloud computing platform, setting up virtual machines and databases, training machine learning algorithms and deploying solutions on the cloud. Most services we discuss provide high-level, user friendly (often graphical) interface. Therefore, no previous knowledge of cloud infrastructure is required.
Dr Radu Tanase
MA students with programming and machine learning knowledge, who are interested in creating software products, assigned to “Wahlpflichtbereich BWL 4”
Work load statement:
|Building relevant programming skills + online exercises||22h|
|Fundamentals of product prototyping||
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, learn how to apply machine learning techniques to a concrete problem, how to create a product prototype and deploy it on the cloud.
- Good programming knowledge in R
- A non-technical introduction to R (or equivalent knowledge)
- Basic knowledge of machine learning
- A non-technical introduction to machine learning (or equivalent knowledge)
Online exercises (30%)
The exercises are assigned on Friday, 18.09.2020.
Deadline to complete the exercises: Wednesday, 07.10.2020, 00:00 CET.
Group Project (60%)
Presentations on Tuesday, 26.11.2020, 16:00 – 20:00.
Peer evaluation (10%)
Dates and Location:
17.09.2020 (16:00 – 18:00) - Kick Off
08.10.2020 (16:00 – 20:00) – Lecture “Fundamentals of product prototyping” followed by discussion of group assignments.
15.10.2020 (16:00 – 18:00) – Project planning.
12.11.2020 – Individual meetings with the groups (the exact time will be set in agreement with the group members).
26.11.2020 (16:00 – 20:00) – Final presentations of group project.
Please see https://studentservices.uzh.ch
The number of participants is limited. Thus, to apply for the seminar, please send your updated CV, transcript of records and short letter of intent to firstname.lastname@example.org . If you receive our positive confirmation, you are asked and allowed to officially book this seminar using the "Modulbuchungstool". Booking the seminar without a positive confirmation from our chair is not implying the right to attend the course. In this case the course will be graded as failed.
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.
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.