Data Science: Advanced Analytics

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TU Dresden | Sommersemester 2023

Data Science: Advanced Analytics

for questions, please contact:

Consultation with Prof. Brendel: on request
(please contact for an appointment)

Course description

The module deals with the basics of unsupervised methods for finding patterns in structured and unstructured data. Students learn methods from the field of machine learning using analytical information systems. Students are able to apply these methods to various practical examples and to evaluate, interpret and critically question the results.

Students are able to analyze unstructured data using text-mining methods. The students have an understanding of problems that can occur in the course of the knowledge-discovery-in-databases process and are able to recognize and solve these problems. Furthermore, the students have knowledge of special procedures in the context of specific application scenarios of machine learning, such as process analysis (process mining) and anomaly detection. They have the ability to design and implement solutions to problems on the basis of structured and unstructured data with selected application systems of machine learning.

Course facts

  • Format: e-Lectures + In-Person exercises + In-Person consultations 
  • Language: English
  • Semester: every summer term
  • Scope: 5 CP

Important information

The number of participants is limited to 60. First come, first serve. There will be a waiting list. This semester in-person exercises and consultations will be offered.

There will be an In-Person Kick-off meeting with all the relevant information about the course. The corresponding information can be found in the timetable.

Final exam

The exam will take place this semester as a hybrid exam in OPAL. Further information will be given during the course.



  • Date: 12.04.2023
  • Hour: 11:10 - 12:40
  • Place: TIL 205 (Entrance via the Hülße-Bau, follow the signs pointing to the Festsaal) 


  • Date: According to Timetable
  • Hour: 11:10 - 12:40
  • Place: Microsoft Teams (link in e-lectures menu)

In-Person Consultations:

  • Dates:
    • 04.05.2023 (Thursday)
    • 11.05.2023 (Thursday)
    • 08.06.2023 (Thursday)
    • 29.06.2023 (Thursday)
    • 20.07.2023 (to be confirmed)
  • Hour: 13:10 - 14:20
  • Place: SCH A200a
Week number Date Holiday Topic
14 05.04.2023 Eastern (Fr.) -
15 12.04.2023 Eastern (Monday) Kick-off
16 19.04.2023   Lecture - Introduction & Segmentation basis
17 26.04.2023   Lecture - Segmentation Methods
18 03.05.2023 1. May (Monday) Lecture - Association Analysis
19 10.05.2023 Dies Academicus (Wednesday) -
20 17.05.2023 Himmelfahrt (Thursday) Exercise 1 - Segmentation
21 24.05.2023   Lecture - Text Mining
22 31.05.2023 Pfingsten (entire week) -
23 07.06.2023   Exercise 2 - Text Mining
24 14.06.2023   Lecture - Deep Learning
25 21.06.2023   Lecture - Anomaly Detection
26 28.06.2023   Lecture - Process Analytics
27 05.07.2023   Exercise 3 - Deep Learning
28 12.07.2023   Trial Exam
29 19.07.2023 Begin of the exam period  

Access to e-lecture videos

After the kick-off, enrolled students will be able to find links to E-lecture videos in the link list. These videos will be hosted at videocampus sachsen.

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