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Data Science
for Accounting and Auditing:
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| Exam
ECTS |
7,5 |
| Examination form |
Written sit-in exam on CBS'
computers |
| Individual or group exam |
Individual exam |
| Assignment type |
Written assignment |
| Duration |
4 hours |
| Grading scale |
7-step scale |
| Examiner(s) |
One internal examiner |
| Exam period |
Winter, One additional external examiner in case
of oral make-up/re-exam |
| Aids |
Closed book: no aids
However, at all
written sit-in exams the student has access to the basic IT
application package (Microsoft Office (minus Excel), digital pen
and paper, 7-zip file manager, Adobe Acrobat, Texlive, VLC player,
Windows Media Player), and the student is allowed to bring simple
writing and drawing utensils (non-digital). PLEASE NOTE: Students
are not allowed to communicate with others during the
exam. |
| Make-up exam/re-exam |
Same examination form as the ordinary exam
If the number of registered candidates for the make-up
examination/re-take examination warrants that it may most
appropriately be held as an oral examination, the programme office
will inform the students that the make-up examination/re-take
examination will be held as an oral examination instead.
Same examination form as the
ordinary exam. If the number of registered candidates for the
make-up/re-examination warrants that it may most appropriately be
held as an oral examination, the programme office will inform the
students that the make-up/re-examination will be held as an oral
examination instead. The re-take follows the same rules as regular
examination
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Modern organizations suffer from phenomena such as data
explosion and information overload. Data scientists have emerged as
a new type of high-ranking professionals with the training and
curiosity to make discoveries in the world of big data. Data
science is an interdisciplinary field aiming to turn data into real
value. Data may be company-internal or external, structured or
unstructured, big or small, static or volatile. Data science deals
with data extraction, preparation, exploration, transformation,
storage, retrieval, computing, mining, learning, presenting,
explaining and predicting.
This course focusses on the implications of data science in the
context of accounting and auditing. A high demand exists in the
marketplace for professionals that are able to deal with and to
analyse large and heterogeneous data especially in the context of
accounting and auditing. This practice-oriented course aims to
provide interested students an entry into data science from an
accounting and auditing perspective. The focus does not lie on
advanced statistical methods and their mathematical foundations.
Instead it focusses on the application of selected data analysis
methods and the necessary theoretical background that is required
to effectively apply these techniques and to interpret the gained
information critically. The course covers topics such as
fundamental aspects of data organisation and retrieval,
characteristics of data science with an overview of descriptive,
predictive and prescriptive analytics, as well as theoretical
foundations and practical applications of selected data analysis
techniques.
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