財務工程專題

Data are everywhere and the ubiquitous availability of huge amounts of data makes it necessary to develop smart data analytics. Out of the plethora of tools that are available for many scientifc disciplines this course offers for the common data analyst an easy access to all levels of analysis without deep computer programming knowledge. SDA provides a wide variety of exercises. In addition a full set of slides is provided making it easier for the participants to reanalyse the presented material. The R and Python programming language are becoming the lingua franca of omputational data analysis. They are the common smart data analysis software platforms used inside corporations and in academia. Both are operating system (OS) independent free open-source programs which are popularised and improved by hundreds of volunteers all over the world. Learnings objectives: ᆞhow to conduct data analysis in a smart fashion ᆞ understand essential programming languages such as Python *use modern technical tools to show and explain your results ᆞsoft skills such as networking, teamwork, defend and sell your project, ...

ᆞThis is a hands-on course with several coding sessions ᆞ Intermediate programming knowledge very welcome (e.g. Python, R languages) ᆞ Economics, engineering or computer science background very welcome ᆞStudents are expected to bring their laptop (MacOS) or have an available workstation to perform the hands-on lab exercises (iCloud)

The following prerequisites are mandatory • iCloud account • Keynote • Laptop (MacBook preferred) • registration in quantinar.com Those prerequisites are mandatory due to the fact that each student has to work on a project (The project needs to be discussed in advance with the course supervisors in order to check for feasibility) in order to complete the course (groups of 2 are feasible for larger projects). The final and working Python code of the project will then be posted on quantlet.de and the student has to present his/her results in class. Projects should be shown in Keynote format and shared with the course supervisors in iCloud. An example Keynote file containing the requested format will be provided to all students.

Homework 70% Term project 30%

地點

By appointment

時間

By appointment

聯絡方式

Prof. Wolfgang Karl Härdle Email: TA Jane's Email: jane.hsieh5288@icloud.com