Syllabus

Title
0850 Computing
Instructors
ao.Univ.Prof. Dr. Josef Leydold
Contact details
Type
PI
Weekly hours
2
Language of instruction
Englisch
Registration
09/17/20 to 09/20/20
Registration via LPIS
Notes to the course
Dates
Day Date Time Room
Monday 10/12/20 02:00 PM - 05:30 PM TC.4.01
Monday 10/19/20 02:00 PM - 05:30 PM TC.5.27
Monday 11/02/20 02:00 PM - 05:30 PM TC.5.27
Monday 11/09/20 02:00 PM - 05:00 PM TC.5.27
Monday 11/16/20 02:00 PM - 05:00 PM TC.5.15
Monday 11/23/20 02:00 PM - 05:00 PM TC.5.27
Monday 11/30/20 02:00 PM - 05:00 PM TC.4.01
Procedure for the course when limited activity on campus

This course will be held in rotation mode, subject to the following specifications:

Students will be assigned to working groups of about 3 students. Based on the assumption that distancing will still be required on Campus, working groups will be collected into 2 classroom groups. Each classroom group meets on campus according to a fixed schedule every second week. Classroom groups not present in the classroom follow the lectures via MS Teams in remote mode. The presentation of your projects will then also be split into two parts then.

However, the expected number of students does not exceed the limited number of seats. In this case the course will take place in the announced lecture hall every week.

All students have to upload their homework solutions on the myLearn platform (i.e., this web site).

The final oral exam will take place in the class room at different times for each working group.

If you are subject to travel restriction, we offer the course in full distance mode. In this case, you will be also member of a working group and a classroom group and you will participate in the classroom meetings via MS Teams at the announced dates. The final exam will than take place online via MS Teams.

 

Contents
  • Block 1: Basic computing and programming: R as an environment for computing and graphics, basic programming structures, input and output
  • Block 2: Typesetting documents with LaTeX and BibTeX
  • Block 3: Functions, more sophisticated data structures and better graphics
  • Block 4: Numerical analysis: Numerical accuracy and program efficiency, root finding and optimization


Learning outcomes

After completing this course the student will have the ability to:

  • Recall the basic constituents of computer programming (data structures and algorithms)
  • Design, implement, test and debug computer programs for solving mathematical/computational problems
  • Perform matrix computations, solve systems of linear and non-linear equations, and optimize functions of one or several variables.

Apart from that, the course will contribute to the students' ability to:

  • demonstrate effective team skills resulting in an appropriate contribution to the production of a group output
  • work and communicate effectively in a team situation and to function as a valuable and cooperative team member
  • participate in group discussions/team work

Moreover, the student will have the ability to:

  • structure given mathematical/computational tasks and develop algorithms for solving them
  • adequately communicate algorithms and computer programs implementing these
  • "turn ideas into software"

In addition, the student will be able to

  • Use R for programming and numerical computations
  • Use LaTeX for creating reports and presentations
  • Use BibTeX for managing bibliographic information


Attendance requirements

For this lecture participation is obligatory. Students are allowed to miss a maximum of 20% (no matter if excused or not excused).

Teaching/learning method(s)

This course is taught as a lecture combined with homework assignments and a course project. In combination with the lecture, homework assignments will help students to consolidate and expand their knowledge and understanding by developing solutions to theoretical and applied problems, and have to be submitted every week via email to the lecturer. Solutions will be discussed in class based on individual students' presentations at the beginning of each unit. For the course project, teams with up to three members will use LaTeX to create a report or presentation of an R-based solution to a given mathematical/computational task.


Assessment
  • 40% home assignments and group discussions
  • 30% course project
  • 30% final exam

The assessment of the homework assignments and course project will be based on the correctness of results, the clarity and persuasiveness of each bit of work and the recognizable effort made. This implies an ability to work in teams. For the final exam, the assessment will be based on the ability to describe and apply the key concepts discussed throughout the course and to choose the appropriate analytical techniques to obtain the relevant data. To avoid the potential free-rider problem related to group work, the final exam will strongly be related to the problems already discussed in homework assignments and course projects.

 

 

Readings
1 Author: Owen Jones, Robert Maillardet, and Andrew Robinson
Title: Introduction to Scientific Programming and Simulation Using R

Publisher: Chapman & Hall/CRC
Edition: ISBN 978-1-4200-6872-6
Remarks: http://www.ms.unimelb.edu.au/spuRs/
Year: 2009
Content relevant for class examination: No
Content relevant for diploma examination: No
Recommendation: Reference literature
Type: Book
2 Author: Tobias Oetiker, Hubert Partl, Irene Hyna and Elisabeth Schlegl
Title: The (Not So) Short Introduction to LaTex2e

Remarks: http://www.ctan.org/tex-archive/info/lshort/english/
Content relevant for class examination: No
Content relevant for diploma examination: No
Recommendation: Strongly recommended (but no absolute necessity for purchase)
Type: Script
Availability of lecturer(s)
josef.leydold@wu.ac.at
Last edited: 2020-07-21



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