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Root number
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478568 |
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Semester
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HS2023 |
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Type of course
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Lecture |
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Allocation to subject
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Economics |
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Type of exam
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Written exam |
| Title |
Programming for Data Scientists I |
| Description |
In this course, you will learn how to program in R and how to use R for effective data analysis. We will cover the following topics:
1) Getting started with R and RStudio
2) Data structures
3) Getting data in and out of R
4) Data transformations
5) Control structures
6) Writing functions
7) Data visualization
8) Exploratory data analysis
9) Simple model building (linear regression)
10) R Markdown
11) Version control with Git (if time permits)
12) Efficient programming: debugging, profiling and parallel computing (if time permits)
You must bring your own laptop to the lectures and the exam. R and RStudio are free.
Suggested textbooks: We do not follow a single textbook during the whole semester but will provide specific references for each part of the course. The following books are particularly useful and are freely available on the internet:
- Hands-On Programming with R by Grolemund
- R Cookbook by Long and Teetor
- R for Data Science by Wickham and Grolemund
- R Programming for Data Science by Peng
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Language: English
Credits: 3 SWS / 4.5 ECTS
Prerequisites: none
Evaluation: online exercises, problem sets and written exam in English
Lecture: Tuesday, 10.15 - 12.00 , 220, H4
**** the lecture December 5, will take place in the Kuppelraum H4 ****
Exercises with assistant Julian Kindlimann (julian.kindlimann@students.unibe.ch), bi-weekly, 201, H4
1st exam: Tuesday, December 19, 2023, 10.15 - 12.00h (105 min), 220, H4
2nd exam: Tuesday, February 13, 2024, 10:15 - 12.00h (105 min), 220, H4 |
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ILIAS-Link (Learning resource for course)
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No registration/deregistration in CTS (Admission in ILIAS possible).
ILIAS
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Link to another web site
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| Lecturers |
Prof. Dr.
Blaise Stéphane Melly, Department of Economics ✉
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ECTS
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4.5 |
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Recognition as optional course possible
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Yes |
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Grading
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1 to 6 |
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| Dates |
Tuesday 10:15-12:00 Weekly
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Thursday 10:15-12:00 Fortnightly
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Tuesday 13/2/2024 10:15-12:00
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| Rooms |
Hörraum 201, Hauptgebäude H4
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Hörraum 220, Hauptgebäude H4
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Kuppelraum 501, Hauptgebäude H4
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| External rooms |
220, H4
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| Students please consult the detailed view for complete information on dates, rooms and planned podcasts. |
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