Please note! Course description is confirmed for two academic years, which means that in general, e.g. Learning outcomes, assessment methods and key content stays unchanged. However, via course syllabus, it is possible to specify or change the course execution in each realization of the course, such as how the contact sessions are organized, assessment methods weighted or materials used.
LEARNING OUTCOMES
The course is intended to provide the student with the basics of applying data analytics in accounting. After completing the course, students will be able to:
- Gain a managerial overview of the potential uses of data analytics in accounting contexts
- Extract, cleanse, and transform heterogeneous data into machine-readable form
- Analyze data to generate information for strategic and operational decision-making
- Understand the potential and pitfalls of machine learning techniques
- Use Python programming language and implement Python modules for data analysis
Credits: 6
Schedule: 01.03.2021 - 16.04.2021
Teacher in charge (valid 01.08.2020-31.07.2022): Jukka Sihvonen
Teacher in charge (applies in this implementation): Jukka Sihvonen
Contact information for the course (valid 19.02.2021-21.12.2112):
Instructor: Jukka Sihvonen
- Email: jukka.sihvonen@aalto.fi
Teaching Assistant: Jaakko Wallenius
- Email: jaakko.wallenius@aalto.fi
CEFR level (applies in this implementation):
Language of instruction and studies (valid 01.08.2020-31.07.2022):
Teaching language: English
Languages of study attainment: English
CONTENT, ASSESSMENT AND WORKLOAD
Content
Valid 01.08.2020-31.07.2022:
The course is an introduction to data analysis with an emphasis on the concepts and techniques
most relevant to accounting analytics. The secondary aim of this course is to acquaint students with Python programming language and its rich ecosystem for data analytics. The general topics of the course are:- Handling large unstructured datasets
- Regression and classification (machine learning)
- Prediction: framework, applications, and evaluation
To achieve these learning objectives, a combination of lectures, online training, in-class exercises, and empirical assignments will be utilized.
Applies in this implementation:
Assessment Methods and Criteria
Valid 01.08.2020-31.07.2022:
- Assignments (40%)
- Lecture diary (20%)
- Final exam (40%)
Student has to pass the final exam and pre-defined assignments for completing the course.
Applies in this implementation:
Workload
Valid 01.08.2020-31.07.2022:
- Lectures approximately 24h
- Lab sessions 12h
- Exam 3h
- Independent work, 121h
Attendance in some contact teaching may be compulsory.
Applies in this implementation:
DETAILS
Study Material
Valid 01.08.2020-31.07.2022:
- Wes McKinney (2017). Python for Data Analysis, 2nd Ed. O’Reilly Media
- Online study resources defined by the instructor
- Material distributed by the instructor
Applies in this implementation:
Prerequisites
Valid 01.08.2020-31.07.2022:
Basic accounting studies are required. Recommended course:
- 22C28000 Accounting and Information Systems, OR
- ABL-C1102 Hands-On-Analytics on Accounting Information Systems
The course builds on Python programming language, but previous coding experience is not a prerequisition. However, the student is required to pass course assignments which include programming components.
Registration for Courses
Valid 01.08.2020-31.07.2022:
Via Sisu. Please see Sisu for the registration dates.
If more students have enrolled by the enrolment deadline than can be accepted on the course, priority will be given to students based on their study right: 1. Accounting MSc students 2. BIZ exchange students 3. Bachelor's students in Accounting who have completed more than 150 cr 4. other BIZ MSc students 5. BIZ Bachelor's students in other majors who have completed more than 150 cr
Applies in this implementation:
During the academic year 2020-2021, the course will be completely online.
The lectures will be recorded and posted online. Therefore, compulsory attendance is not required.
FURTHER INFORMATION
Further Information
Valid 01.08.2020-31.07.2022:
It is recommended to bring your own laptop to the lectures. Work with your own laptop during the course if possible.
Course is open for BIZ students only in 2020-21.
Applies in this implementation:
During the academic year 2020-2021, the course will be completely online.
The lectures will be recorded and posted online. Therefore, compulsory attendance is not required.
Details on the schedule
Applies in this implementation:
- Teacher: Sihvonen Jukka
- Teacher: Vuolteenaho Tomi