2021/2022 BA-BINTV2006U Programming and Data Analysis for Business
English Title | |
Programming and Data Analysis for Business |
Course information |
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Language | English |
Course ECTS | 7.5 ECTS |
Type | Elective |
Level | Bachelor |
Duration | One Semester |
Start time of the course | Autumn |
Timetable | Course schedule will be posted at calendar.cbs.dk |
Max. participants | 120 |
Study board |
Study Board for BSc/MSc in Business Administration and
Information Systems, BSc
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Course coordinator | |
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Main academic disciplines | |
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Teaching methods | |
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Last updated on 04-02-2021 |
Relevant links |
Learning objectives | |||||||||||||||||||||||||
After the course the students should be able to:
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Course prerequisites | |||||||||||||||||||||||||
None | |||||||||||||||||||||||||
Prerequisites for registering for the exam (activities during the teaching period) | |||||||||||||||||||||||||
Number of compulsory
activities which must be approved (see section 13 of the Programme
Regulations): 3
Compulsory home
assignments
Each student has to get 3 out of 5 individual quizzes approved in order to qualify for the final exam. The quizzes will contain both multiple choice, multiple answers and fill out blanks. They will cover: 1. Users and programming environment 2. Variables, data types and conditions 3. Loops, functions and objects. 4. Prognoses and inference 5. Applikations Retake of quizzes: There will not be any extra attempts provided to the students before the ordinary exam. If a student cannot participate in the compulsory assignments due to documented illness, or if a student does not have the activities approved in spite of making a real attempt, then the student will be given one extra attempt before the re-exam. Before the re-exam, there will be one home assignment (max.10 pages) which will cover 3 mandatory assignments. |
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Examination | |||||||||||||||||||||||||
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Course content, structure and pedagogical approach | |||||||||||||||||||||||||
Starting from scratch, the students will after the course have the basis for working with simple data analysis and programming
The course can be used as a basis for more advanced courses where programming, mathematical modelling, and data handling is increasingly important, for instance finance, economy, information systems, communications, etc. |
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Description of the teaching methods | |||||||||||||||||||||||||
The course will use blended elements to introduce
basic concepts and get hands on.
Also, the method paired programming will be used for some of the F2F exercises in which two students take turns programming and instructing the programming. There will be on site exercise hours in which the students can work with exercises and get help from instructor and peers. |
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Feedback during the teaching period | |||||||||||||||||||||||||
There will be feed back to the mandatory quizzes,
which cover roughly all of curriculum. Additionally, there will be
feed back to the student presentation of their project exercise.
Additionally, oral feed back on programming excersises will be given in class. |
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Student workload | |||||||||||||||||||||||||
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Further Information | |||||||||||||||||||||||||
Motivated in business, the programming course is relevant for students from bachelor programs such as BSc in Digital management, HA-almen, BSc SOC, SEM, IB, IBP, and other, who might have an interest in using high end tools for data anlysis. |
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Expected literature | |||||||||||||||||||||||||
The literature can be changed before the semester starts. Students are advised to find the final literature on Canvas before they buy any material.
Garrett Grolemund; Hadley Wickham: , R for Data Science, O'Reilly, 2017 https://r4ds.had.co.nz/
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