Advanced Programming in R, 6 credits (732A94)

Avancerad programmering i R, 6 hp

Course description

The course is devoted to studying the programming language R, including its standard and more advanced tools. The course is a mix of lectures and exercise sessions. Such concepts as reading data from file and from the internet, data structures, functions and objects, debugging, object-oriented programming, performance enhancement, parallel programming and many other concepts are studied in the course.

Main field of study

Computer Science

Level

Second cycle

Course type

Single subject and programme course

Examiner

Krzysztof Bartoszek

Course coordinator

Krzysztof Bartoszek

Director of studies or equivalent

Jolanta Pielaszkiewicz

Available for exchange students

Yes
Course offered for Semester Weeks Language Campus VOF
Single subject course (Half-time, Day-time) Autumn 2020 v202035-202044 English Linköping
Single subject course (Half-time, Day-time) Autumn 2020 v202035-202044 English Linköping
F7MSL Statistics and Machine Learning, Master´s Programme - First and main admission round 1 (Autumn 2020) v202035-202044 English Linköping v
F7MSL Statistics and Machine Learning, Master´s Programme - Second admission round (open only for Swedish/EU students) 1 (Autumn 2020) v202035-202044 English Linköping v

Main field of study

Computer Science

Course level

Second cycle

Advancement level

A1X

Course offered for

  • Master's Programme in Statistics and Machine Learning

Entry requirements

  • Bachelor's degree equivalent to a Swedish Kandidatexamen of 180 ECTS credits including an in-depth academic paper 15 ECTS credits in 
    • statistics
    • mathematics
    • applied mathematics
    • computer science
    • engineering 
  • Passed courses in
    • calculus
    • linear algebra
    • statistics 
    • programming
  • English corresponding to the level of English in Swedish upper secondary education (Engelska 6/B)
    (Exemption from Swedish)

Intended learning outcomes

After completion of the course the student should on an advanced level be able to:

  • write R programs based on programming techniques such as reading data from file or Internet, assignment and manipulation of data structures, defining own functions, iterations, conditional (if-then-else) statements and debugging,
  • speed up R programs by using parallel programming and performance enhancement tools,
  • organize the own code in the form of an R package.

Course content

The course introduces general programming techniques and their practical implementation in the R language.

More specifically, the course includes:

  • reading data from file, from the internet, and printing to output,
  • data structures, functions and objects,
  • iteration and conditional statements,
  • numerical linear algebra in R,
  • debugging,
  • object-oriented programming,
  • performance enhancement,
  • parallel programming,
  • literate programming,
  • development of R packages.

Teaching and working methods

The teaching comprises lectures and computer exercises. The lectures are devoted to presentations of concepts and methods. The computer exercises provide practical experience of programming in R. Homework and independent study are a necessary complement to the course.
Language of instruction: English.

Examination

Written reports on computer exercises. One final written or oral examination. Detailed information about the examination can be found in the course’s study guide.

If the LiU coordinator for students with disabilities has granted a student the right to an adapted examination for a written examination in an examination hall, the student has the right to it. If the coordinator has instead recommended for the student an adapted examination or alternative form of examination, the examiner may grant this if the examiner assesses that it is possible, based on consideration of the course objectives.

Students failing an exam covering either the entire course or part of the course twice are entitled to have a new examiner appointed for the reexamination.

Students who have passed an examination may not retake it in order to improve their grades.

Grades

ECTS, EC

Other information

Planning and implementation of a course must take its starting point in the wording of the syllabus. The course evaluation included in each course must therefore take up the question how well the course agrees with the syllabus.

The course is carried out in such a way that both men´s and women´s experience and knowledge is made visible and developed.

Department

Institutionen för datavetenskap
There is no course literature available for this course.
DAT3 Computer Exam EC 3 credits
LAB1 Laboratory work EC 3 credits

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