700.395 (19S) Data Mining and Neurocomputing
Overview
- Lecturer
- Course title german Data Mining and Neurocomputing
- Type Lecture - Course (continuous assessment course )
- Hours per Week 2.0
- ECTS credits 4.0
- Registrations 23 (25 max.)
- Organisational unit
- Language of instruction English
- Course begins on 07.05.2019
- eLearning Go to Moodle course
- Seniorstudium Liberale Yes
Time and place
Course Information
Intended learning outcomes
Data Mining and Neurocomputing have different applications in text categorization, e.g., spam filtering, fraud detection, optical character recognition, machine vision, e.g., face detection, licenses plate recognition, advanceddriver assistance systems, natural-language processing, e.g., spoken language understanding, market segmentation, e.g., predict if a customer will get a credit, and bioinformatics, e.g., classify proteins or lipidomes according to their function.
The lecture will (a) explain the basic approaches of Data Mining and Neurocomputing models, (b) guide to transfer the acquired knowledge to solve classification problems for industry and research, and (c) show some use-cases and interesting applications from the state-of-the-art.
Teaching methodology including the use of eLearning tools
Theory + practical examples (Matlab +Python)
Course content
- Data preprocessing
- Unsupervised Learning and Clustering
- Supervised Learning (SVM, Bayes, Decision Trees, CNN, etc)
- Reinforcement Learning
- Deep Learning
- Time series forecast
- Evaluation Metrics
Examination information
Grading scheme
Grade / Grade grading schemePosition in the curriculum
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 4) (
0.0h VK, VO, KU / 14.0 ECTS)
-
Subject: Information and Communications Engineering: Supplements (NC, ASR)
(Compulsory elective)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (Anhang 5) (
0.0h VK, VO, KU / 12.0 ECTS)
-
Subject: Technical Complements (NC, ASR)
(Compulsory elective)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Autonomous Systems and Robotics: Advanced (ASR)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
-
Subject: Autonomous Systems and Robotics: Advanced (ASR)
(Compulsory elective)
- Masterstudium Information and Communications Engineering (ICE)
(SKZ: 488, Version: 15W.1)
-
Subject: Autonomous Systems and Robotics (WI)
(Compulsory elective)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
Wahl aus dem LV-Katalog (siehe Anhang 3) (
0.0h VK, VO / 30.0 ECTS)
-
Subject: Autonomous Systems and Robotics (WI)
(Compulsory elective)
- Master's degree programme Information Technology
(SKZ: 489, Version: 06W.3)
-
Subject: Research Track (Methodological focus)
(Compulsory subject)
-
4.2'-4.3' Theoretical methodological courses I/II (
0.0h VO/VK/VS/KU/PS / 6.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
4.2'-4.3' Theoretical methodological courses I/II (
0.0h VO/VK/VS/KU/PS / 6.0 ECTS)
-
Subject: Research Track (Methodological focus)
(Compulsory subject)
- Masterstudium Mathematics
(SKZ: 401, Version: 18W.1)
-
Subject: Information and Communications Engineering
(Compulsory elective)
-
9.5 Data Mining and Neurocomputing (
2.0h VC / 4.0 ECTS)
- 700.395 Data Mining and Neurocomputing (2.0h VC / 4.0 ECTS)
-
9.5 Data Mining and Neurocomputing (
2.0h VC / 4.0 ECTS)
-
Subject: Information and Communications Engineering
(Compulsory elective)
Equivalent courses for counting the examination attempts
-
Wintersemester 2023/24
- 700.395 VC Data Mining, Synthetic Data, and Knowledge Discovery (2.0h / 4.0ECTS)
-
Wintersemester 2022/23
- 700.395 VC Data Mining, Synthetic Data and Knowledge Discovery (2.0h / 4.0ECTS)
-
Wintersemester 2021/22
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Wintersemester 2020/21
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Sommersemester 2020
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Wintersemester 2017/18
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Wintersemester 2016/17
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Wintersemester 2015/16
- 700.395 VC Data Mining and Neurocomputing (2.0h / 4.0ECTS)
-
Wintersemester 2013/14
- 700.395 VK Data Mining in Intelligent Transportation and Logistics (2.0h / 4.0ECTS)
-
Wintersemester 2012/13
- 700.395 VK Data Mining in Intelligent Transportation and Logistics (2.0h / 4.0ECTS)