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lecture and readme: Pushed the basic updates (dates/lecturers) for 20…
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dominik-probst committed Mar 26, 2024
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# Other files
*.db
*.cspell/
.DS_Store
53 changes: 28 additions & 25 deletions README.org
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#+title: KDD - Knowledge Discovery in Databases

* Responsibilities
(Changed in 2024WS since Melanie B. Sigl is not participating this time)
** Lecture
1. *Course Intro* - Dominik Probst
2. *Introduction* - Dominik Probst
3. *Data* - Melanie B. Sigl
3. *Data* - Dominik Probst
4. *Preprocessing* - Dominik Probst
5. *OLAP* - Melanie B. Sigl
5. *OLAP* - Dominik Probst
6. *Mining Frequent Patterns, Associations and Correlations* - Dominik Probst
7. *Classification* - Melanie B. Sigl
7. *Classification* - Dominik Probst
8. *Cluster Analysis* - Dominik Probst
9. *Outlier Analysis* - Melanie B. Sigl
9. *Outlier Analysis* - Dominik Probst
10. *Current Research at CS6* - Dominik Probst

** Exercise
1. *Introduction to Python & Pandas* - Melanie B. Sigl
1. *Introduction to Python & Pandas* - Dominik Probst
2. *Data analysis & data preprocessing* - Dominik Probst
3. *Frequent Patterns* - Dominik Probst
4. *Classification* - Melanie B. Sigl
4. *Classification* - Dominik Probst
5. *Clustering* - Dominik Probst
6. *Outlier* /(suspended)/ - Melanie B. Sigl

* Summer semester 2023
- Semester duration: 17 April 2023 – 21 July 2023
- No lectures on: Tuesday, 30 May 2023 (CW 22)
* Summer semester 2024
- Semester duration: 15 April 2024 – 19 July 2024
- Public holidays:
- Monday, 1 May 2023 (Tag der Arbeit/May Day, CW 18)
- Thursday, 18 May 2023 (Christi Himmelfahrt/Ascension Day, CW 20)
- Monday, 29 May 2022 (Pfingstmontag/Whit Monday, CW 22)
- Thursday, 8 June 2022 (Fronleichnam/Corpus Christi, CW 23)
- Wednesday, 1 May 2024
- Thursday, 9 May 2024
- Monday, 20 May 2024
- Thursday, 30 May 2024
- FAU specific holidays (no lectures and exercises):
- Tuesday, 21 May 2024
- Friday, 31 May 2024

| *Calendar Week* | *Lecture Topic* | *Lecturer* | *Exercise* |
|---------------+----------------------------------------+----------------------------------+------------------------------------|
| 16 | Course Introduction + KDD Introduction | Dominik Probst | |
| 17 | Data | Melanie B. Sigl | Introduction to Python & Pandas |
| 17 | Data | Dominik Probst | Introduction to Python & Pandas |
| 18 | Preprocessing, Part 1 | Dominik Probst | Data analysis & data preprocessing |
| 19 | Preprocessing, Part 2 | Dominik Probst | Data analysis & data preprocessing |
| 20 | OLAP | Melanie B. Sigl | Data analysis & data preprocessing |
| 21 | Frequent Pattern, Part 1 | Dominik Probst | - |
| 22 | Frequent Pattern, Part 2 | Dominik Probst | Frequent Pattern |
| 23 | Classification, Part 1 | Melanie B. Sigl | Frequent Pattern |
| 24 | Classification, Part 2 | Melanie B. Sigl | Classification |
| 25 | Cluster Analysis, Part 1 | Dominik Probst | Classification |
| 26 | Cluster Analysis, Part 2 | Dominik Probst | Classification |
| 27 | Outlier Analysis, Part 1 | Melanie B. Sigl | Clustering |
| 28 | Outlier Analysis, Part 2 | Melanie B. Sigl | Clustering |
| 29 | Current Research at CS6 and Exam QnA | Melanie B. Sigl + Dominik Probst | |
| 20 | OLAP | Dominik Probst | Data analysis & data preprocessing |
| 21 | - | Dominik Probst | - |
| 22 | Frequent Pattern, Part 1 | Dominik Probst | - |
| 23 | Frequent Pattern, Part 2 | Dominik Probst | Frequent Pattern |
| 24 | Classification, Part 1 | Dominik Probst | Frequent Pattern |
| 25 | Classification, Part 2 | Dominik Probst | Classification |
| 26 | Cluster Analysis, Part 1 | Dominik Probst | Classification |
| 27 | Cluster Analysis, Part 2 | Dominik Probst | Classification |
| 28 | Outlier Analysis, Part 1 | Dominik Probst | Clustering |
| 29 | Outlier Analysis, Part 2 & Exam QnA (if there is time) | Dominik Probst | Clustering |


* Setup for Building Lecture Slides Locally
To build these lecture slides locally on your machine you'll need an up-to-date
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106 changes: 44 additions & 62 deletions lecture/1-prologue/1-prologue.tex
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\begin{frame}{Who? - Lecturers}
%Melanie Bianca Sigl
\begin{columns}[T]
\begin{column}{0.2\textwidth}
\vspace{-1em}
\begin{figure}[T]
\centering
\includegraphics[width=0.55\textwidth]{img/melanie_b_sigl.jpg}
\end{figure}
\end{column}
\begin{column}{0.8\textwidth}
\textbf{Melanie Bianca Sigl, M.Sc.}
\begin{itemize}
\item External Ph.D. candidate at Computer Science 6 (Data Management)
\item Managing Consultant at PRODATO Integration Technology GmbH
\item E-Mail: \texttt{\href{mailto:[email protected]}{[email protected]}}
\item Website: \url{https://www.cs6.tf.fau.eu/person/melanie-sigl/}
\end{itemize}
\end{column}
\end{columns}

\vspace{2em}
\begin{frame}{Who? - Lecturer}

%Dominik Probst
\begin{columns}[T]
Expand All @@ -37,7 +16,7 @@
\item Ph.D. candidate
\item Computer Science 6 (Data Management)
\item E-Mail: \texttt{\href{mailto:[email protected]}{[email protected]}}
\item Website: \url{https://www.cs6.tf.fau.de/person/dominik-probst/}
\item Website: \url{https://www.cs6.tf.fau.eu/dp}
\end{itemize}
\end{column}
\end{columns}
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\item \textbf{Mandatory requirements:}
\begin{itemize}
\item Successful completion of the module \glqq Konzeptionelle Modellierung\grqq~(KonzMod)
\begin{itemize}
\item Or a similar course teaching the basics of databases and SQL
\end{itemize}
\end{itemize}
\item \textbf{Useful prerequisites:}
\begin{itemize}
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\vspace*{-1\multicolsep}
\begin{multicols}{2}
\begin{enumerate}
\item Introduction {\color{gray} - D. Probst}
\item Data {\color{gray} - M. B. Sigl}
\item Preprocessing {\color{gray} - D. Probst}
\item Data Warehousing {\color{gray} - M. B. Sigl}
\item Mining Frequent Patterns {\color{gray} - D. Probst}
\item Classification {\color{gray} - M. B. Sigl}
\item Cluster Analysis {\color{gray} - D. Probst}
\item Outlier Analysis {\color{gray} - M. B. Sigl}
\item {\color{gray}Guest lecture by Dr. Katharina Strohriegl (Brose Fahrzeugteile GmbH Co. KG)}
\item Introduction
\item Data
\item Preprocessing
\item Data Warehousing
\item Mining Frequent Patterns
\item Classification
\item Cluster Analysis
\item Outlier Analysis
\item {\color{gray}Guest lecture by ???}
\end{enumerate}
\end{multicols}
\vspace*{-1\multicolsep}
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\begin{itemize}
\item \textbf{Lecture} - Start in Calendar Week 16 (Today)
\begin{itemize}
\item Friday, 12:15 - 13:45 (H8) \\
{\color{gray}Lecturers: M. B. Sigl and D. Probst}
\item Monday, 10:15 - 11:45 (H20) \\
{\color{gray}Lecturer: D. Probst}
\end{itemize}
\end{itemize}
\end{column}

\begin{column}{0.5\textwidth}
\begin{itemize}
\item \textbf{Exercises} - Start in Calendar Week 18
\item \textbf{Exercises} - Start in Calendar Week 17 (Optional)
\begin{itemize}
\item Tuesday, 12:15 - 13:45 (0.031-113) \\
{\color{gray}Tutors: Lucas Weber}
\item Wednesday, 12:15 - 13:45 (H4) \\
{\color{gray}Tutors: Supraja Ramesh}
\item Thursday, 16:15 - 17:45 (H8) \\
{\color{gray}Tutors: D. Probst}
\item Friday, 14:15 - 15:45 (H5) \\
{\color{gray}Tutors: M. B. Sigl and D. Probst}
\item Monday, 16:15 - 17:45 (H4) \\
{\color{gray}Tutor: Dominik Probst}
\item Tuesday, 12:15 - 13:45 (H18) \\
{\color{gray}Tutor: Lucas Weber}
\item Wednesday, 08:15 - 09:45 (H4) \\
{\color{gray}Tutor: Anugya Sahu}
\item Wednesday, 16:15 - 17:45 (H4) \\
{\color{gray}Tutor: Karan Pahlajani}
\end{itemize}
\end{itemize}
\end{column}
\end{columns}

\begin{block}{Registration for Exercises}
Registration for exercises is mandatory to ensure an appropriate support to questions regarding setting of exercises should they arise.
{\color{faured}Registration opens at April 21th, 14:00 o'clock via StudOn.}
{\color{faured}Registration opens at April 15th, 12:00 o'clock via StudOn.}
\end{block}
\end{frame}

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\centering
\begin{tabular}{|p{4em}|p{25em}|p{21em}|}
\hline
\rowcolor{faugray!62}\textbf{Calendar Week} & \textbf{Lecture} & \textbf{Exercise} \\ \hhline{*{3}{:=}:}
\cellcolor{faugray!25}16 & Prologue + Introduction & \cellcolor{gray!50} \\ \hline
\cellcolor{faugray!25}17 & Data &
Introduction to python \& pandas {\color{gray}(optional)} \\ \hline
\cellcolor{faugray!25}18 & \multirow{2}{*}{Preprocessing} & \multirow{3}{*}[-0.6em]{Data Analysis \& Data Preprocessing} \\
\cellcolor{faugray!25}19 & & \\ \hhline{|--|~|}
\cellcolor{faugray!25}20 & \textcolor{gray}{Guest lecture (Brose Fahrzeugteile GmbH Co. KG)} +\newline Data Warehousing & \\ \hline
\cellcolor{faugray!25}21 & \multirow{2}{*}{Frequent Pattern} & \cellcolor{gray!50} \\ \hhline{|-|~|-|}
\cellcolor{faugray!25}22 & & \multirow{2}{*}{Frequent Pattern} \\ \hhline{|-|-|~|}
\cellcolor{faugray!25}23 & \multirow{2}{*}{Classification} & \\ \hhline{|-|~|-|}
\cellcolor{faugray!25}24 & & \multirow{3}{*}{Classification} \\ \hhline{|-|-|~|}
\cellcolor{faugray!25}25 & \multirow{2}{*}{Cluster Analysis} & \\ \hhline{|-|~|}
\cellcolor{faugray!25}26 & & \\ \hline
\cellcolor{faugray!25}27 & \multirow{2}{*}{Outlier Analysis} & \multirow{2}{*}{Clustering} \\ \hhline{|-|~|}
\cellcolor{faugray!25}28 & & \\ \hline
\cellcolor{faugray!25}29 & \textcolor{gray}{Current Research at CS6 and Exam Q\&A} & \cellcolor{gray!50} \\ \hline
\rowcolor{faugray!62}\textbf{Calendar Week} & \textbf{Lecture} & \textbf{Exercise} \\ \hhline{*{3}{:=}:}
\cellcolor{faugray!25}16 & Prologue + Introduction & \cellcolor{gray!50} \\ \hline
\cellcolor{faugray!25}17 & Data &
Introduction to python \& pandas {\color{gray}(optional)} \\ \hline
\cellcolor{faugray!25}18 & \multirow{2}{*}{Preprocessing} & \multirow{3}{*}[-0.6em]{Data Analysis \& Data Preprocessing} \\
\cellcolor{faugray!25}19 & & \\ \hhline{|--|~|}
\cellcolor{faugray!25}20 & \textcolor{gray}{Guest lecture} +\newline Data Warehousing & \\ \hline
\cellcolor{faugray!25}21 & \cellcolor{gray!50} & \cellcolor{gray!50} \\ \hline
\cellcolor{faugray!25}22 & \multirow{2}{*}{Frequent Pattern} & \cellcolor{gray!50} \\ \hhline{|-|~|-|}
\cellcolor{faugray!25}23 & & \multirow{2}{*}{Frequent Pattern} \\ \hhline{|-|-|~|}
\cellcolor{faugray!25}24 & \multirow{2}{*}{Classification} & \\ \hhline{|-|~|-|}
\cellcolor{faugray!25}25 & & \multirow{3}{*}{Classification} \\ \hhline{|-|-|~|}
\cellcolor{faugray!25}26 & \multirow{2}{*}{Cluster Analysis} & \\ \hhline{|-|~|}
\cellcolor{faugray!25}27 & & \\ \hline
\cellcolor{faugray!25}28 & \multirow{2}{*}{Outlier Analysis \textcolor{gray}{+ Exam Q\&A }} & \multirow{2}{*}{Clustering} \\ \hhline{|-|~|}
\cellcolor{faugray!25}29 & & \\ \hline
\end{tabular}
\end{frame}

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\begin{columns}
\begin{column}{0.7\textwidth}
\begin{itemize}
\item Register at: \url{https://www.studon.fau.de/crs4941254_join.html}
\item Register at: \url{https://www.studon.fau.de/crs5533883_join.html}
\item Main source for resources. E.g.:
\begin{itemize}
\item Zoom access data
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\end{column}
\begin{column}{0.3\textwidth}
\begin{center}
\qrcode{https://www.studon.fau.de/crs4941254_join.html}
\qrcode{https://www.studon.fau.de/crs5533883_join.html}
\end{center}
\end{column}
\end{columns}
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2 changes: 1 addition & 1 deletion lecture/x-additional/date.tex
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\date[SS2023]{Summer semester 2023}
\date[SS2024]{Summer semester 2024}

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