====== Programming ======
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| [[https://ekvv.uni-bielefeld.de/kvv_publ/publ/vd?id=228809714|392168]]/[[https://ekvv.uni-bielefeld.de/kvv_publ/publ/vd?id=228811295|392169]] | Schönhuth /Knop | Winter 2020/21 | Wed 14:15-15:45 (Q&A) and Thu 10:15-11:45 (Ü) in ZOOM |

==== Contents ====

Data Science is an emerging interdisciplinary field with the aim to extract information from prevalently unstructured data. A basic skill for every data scientist is programming.

This course sets out to introduce Python, a modern object-oriented programming language, to prospective data scientists. The class covers basic programming skills and provides an introduction to computer science. In the second part, Python libraries and tools are presented that are handy in the daily life of a data scientist, such as Jupyter Notebook, NumPy, Pandas, Matplotlib, Scikit-Learn, and Pyspark.
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//No prior knowledge of computer science is required, but basic training in mathematics is assumed.//

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**This class will be taught online, through video lectures plus a weekly Q&A-Session in ZOOM**
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**Tutorials are offered in form of video conferences.**
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==== Important Links ====

[[https://lernraumplus.uni-bielefeld.de/course/view.php?id=7725 | Lernraum-Plus]]\\
[[ https://uni-bielefeld.cloud.panopto.eu/Panopto/Pages/Sessions/List.aspx?folderID=4af492a7-5891-4e41-b380-ac6400e23e66 | Panopto ]]
==== Literature ====

  * VanderPlas, Jake. (2016). Python data science handbook. Beijing; Boston; Farnham; Sebastopol; Tokyo: O’Reilly: https://jakevdp.github.io/PythonDataScienceHandbook/
  * Toomey, Dan. (2017). Jupyter for data science. Birmingham; Mumbai: Packt: https://katalogplus.ub.uni-bielefeld.de/title/2539316
  * Ana Bell, Eric Grimson, John Guttag (2016) MIT 6.0001 Introduction to Computer Science and Programming in Python: http://ocw.mit.edu/6-0001F16
  * Eric Grimson, John Guttag, Ana Bell (2016) MIT 6.0002 Introduction to Computational Thinking and Data Science: http://ocw.mit.edu/6-0002F16

==== Time table ====

| **Date** | **Topic** | **Exercises** |
| 11.11.2020 | [[teaching:2020winter:prog:lecture01|Logistics, Introduction]] ({{teaching:2020winter:prog:slides01.pdf|slides}},{{teaching:2020winter:prog:introduction.pdf|slides meeting}})| {{teaching:2020winter:prog:exercises01.pdf|Ex01}}|
| 18.11.2020 | [[teaching:2020winter:prog:lecture02|Programming & Python Basics I]] ({{teaching:2020winter:prog:slides02.pdf|slides}}) | {{teaching:2020winter:prog:exercises02.pdf|Ex02}} |
| 25.11.2020 | [[teaching:2020winter:prog:lecture03|Programming & Python Basics II]] ({{teaching:2020winter:prog:slides03.pdf|slides}}, {{teaching:2020winter:prog:course_material_03.zip|material}}) | {{teaching:2020winter:prog:exercises03.pdf|Ex03}} |
| 02.12.2020 | [[teaching:2020winter:prog:lecture04| Data management & Analysis]] ({{teaching:2020winter:prog:slides04.pdf|slides}}, {{teaching:2020winter:prog:course_material_04.zip|material}}) | {{teaching:2020winter:prog:exercises04.pdf|Ex04}}, {{teaching:2020winter:prog:exercise_material_04.zip|material}}|
| 09.12.2020 | [[teaching:2020winter:prog:lecture05| Numerical Data Analysis & Visualization]] ({{teaching:2020winter:prog:slides05.pdf|slides}}, {{teaching:2020winter:prog:course_material_05.zip|material}}) | {{teaching:2020winter:prog:exercises05.pdf|Ex05}}, {{teaching:2020winter:prog:exercise_material_05.zip|material}} |
| 16.12.2020 | [[teaching:2020winter:prog:lecture06| Tabular Data Analysis]] ({{teaching:2020winter:prog:slides06.pdf|slides}}, {{teaching:2020winter:prog:course_material_06.zip|material}})| {{teaching:2020winter:prog:exercises06.pdf|Ex06}}, {{teaching:2020winter:prog:exercise_material_06.zip|material}}  |
| 23.12.2020 - 04.01.2021| Christmas Break ||
| 06.01.2021 | [[teaching:2020winter:prog:lecture07| Applied Machine Learning]] ({{teaching:2020winter:prog:slides07.pdf|slides}}, {{teaching:2020winter:prog:course_material_07.zip|material}})| {{teaching:2020winter:prog:exercises07.pdf|Ex07}} |
| 13.01.2021 | [[teaching:2020winter:prog:lecture08|Databases & Distributed Computing]] ({{teaching:2020winter:prog:slides08.pdf|slides}}, {{teaching:2020winter:prog:course_material_08.zip|material}}) | {{teaching:2020winter:prog:exercises08.pdf|Ex08}}, {{teaching:2020winter:prog:exercise_material_08.zip|material}}  |
| 20.01.2021 | [[teaching:2020winter:prog:lecture09|Advanced Programming]] ({{teaching:2020winter:prog:slides09.pdf|slides}}, {{teaching:2020winter:prog:course_material_09.zip|material}}) | {{teaching:2020winter:prog:exercises09.pdf|Ex09}} |
| 27.01.2021 | [[teaching:2020winter:prog:lecture10|Algorithms & Complexity]] | |
| 03.02.2021 | Exam Preparation ||
| 10.02.2021 | Exam ||