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Machine learning and data mining: concepts, models, learning methods
Course
3

Booking no:

36136

Machine learning and data mining: concepts, models, learning methods

Develop a sound technical understanding of artificial intelligence. In this course, you will not only learn how data mining, neural networks and models really work, but also use them to implement practical projects yourself. After completing the course, you will be able to understand AI processes in detail, make informed decisions about the use of AI and communicate with technicians on an equal footing.

4 weeks
approx. 20 hours
Online
German
Professional and Master Class

Date preview

Start date
Last module
Availability
Location
12.6.2025
10.7.2025
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implementation
Live-Online
12.6.2025
10.7.2025
Fully booked
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implementation
Live-Online
3.7.2025
31.7.2025
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implementation
Live-Online
7.8.2025
5.9.2025
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implementation
Live-Online
7.8.2025
4.9.2025
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implementation
Live-Online
4.9.2025
2.10.2025
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implementation
Live-Online
4.9.2025
2.10.2025
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implementation
Live-Online
18.9.2025
23.10.2025
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implementation
Live-Online
30.10.2025
27.11.2025
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implementation
Live-Online
20.11.2025
18.12.2025
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implementation
Live-Online
20.11.2025
18.12.2025
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implementation
Live-Online
15.1.2026
12.2.2026
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implementation
Live-Online
15.1.2026
12.2.2026
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implementation
Live-Online
19.2.2026
19.3.2026
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implementation
Live-Online
12.3.2026
9.4.2026
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Maximum planning security
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Next booking secures the
implementation
Live-Online
2.4.2026
30.4.2026
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Maximum planning security
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Next booking secures the
implementation
Live-Online

Module overview

The following module overview shows dates for the course start on
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Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 12.06.2025
09:00 am - 11:00 am

61420601
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 12.06.2025
1:00 pm - 3:00 pm

61402020
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 03.07.2025
09:00 am - 11:00 am

61420602
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 07.08.2025
11:30 am - 1:30 pm

61420603
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 07.08.2025
09:00 am - 11:00 am

61402021
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 04.09.2025
3:30 pm - 5:30 pm

61420604
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 04.09.2025
1:00 pm - 3:00 pm

61402022
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 18.09.2025
4:00 pm - 6:00 pm

61420605
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 30.10.2025
09:00 am - 11:00 am

61424564
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 20.11.2025
09:00 am - 11:00 am

61424565
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 20.11.2025
11:30 a.m. - 1:30 p.m.

61424566
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 15.01.2026
09:00 am - 11:00 am

61424567
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 15.01.2026
11:30 a.m. - 1:30 p.m.

61424568
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 19.02.2026
09:00 am - 11:00 am

61424569
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 12.03.2026
09:00 am - 11:00 am

61424570
Module
1

Kick-off, introduction and introduction to KNIME

After the introduction and an introduction to the learning environment, we get straight into the topic: Your:e trainer will go through a first complete pipeline with you, from data preparation to training the data model. 

Webinar
120 min.

Thursday, 02.04.2026
09:00 am - 11:00 am

61424571
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61420601
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61402020
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61420602
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61420603
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61402021
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61420604
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61402022
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61420605
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61424564
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61424565
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61424566
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61424567
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61424568
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61424569
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61424570
Module
2

Basics: machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?
Self-study phase
120 minutes
61424571
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61420601
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61402020
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61420602
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61420603
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61402021
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61420604
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61402022
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61420605
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61424564
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61424565
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61424566
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61424567
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61424568
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61424569
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61424570
Module
3

Data Understanding and Data Preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects
Self-study phase
240 minutes
61424571
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 26.06.2025
12:30 p.m. - 3:30 p.m.

61420601
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 26.06.2025
09:00 am - 12:00 pm

61402020
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 17.07.2025
09:00 am - 12:00 pm

61420602
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 21.08.2025
12:30 p.m. - 3:30 p.m.

61420603
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 21.08.2025
09:00 am - 12:00 pm

61402021
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 18.09.2025
12:30 p.m. - 3:30 p.m.

61420604
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 18.09.2025
09:00 am - 12:00 pm

61402022
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 02.10.2025
4:00 pm - 7:00 pm

61420605
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 13.11.2025
09:00 am - 12:00 pm

61424564
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 04.12.2025
09:00 am - 12:00 pm

61424565
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 04.12.2025
1:00 pm - 4:00 pm

61424566
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 29.01.2026
09:00 am - 12:00 pm

61424567
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 29.01.2026
1:00 pm - 4:00 pm

61424568
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 05.03.2026
09:00 am - 12:00 pm

61424569
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 26.03.2026
09:00 am - 12:00 pm

61424570
Module
4

Discussion of the practical tasks

After reflecting together on the content from the first self-study phases, your:e trainer will introduce you to practical work with the most important data tools. This will give you the knowledge you need to complete your own projects.

Webinar
180 min.

Thursday, 16.04.2026
09:00 am - 12:00 pm

61424571
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61420601
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61402020
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61420602
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61420603
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61402021
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61420604
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61402022
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61420605
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61424564
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61424565
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61424566
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61424567
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61424568
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61424569
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61424570
Module
5

Modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME
Self-study phase
300 min.
61424571
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61420601
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61402020
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61420602
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61420603
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61402021
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61420604
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61402022
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61420605
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61424564
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61424565
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61424566
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61424567
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61424568
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61424569
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61424570
Module
6

Basics of neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
Self-study phase
60 min.
61424571
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 10.07.2025
12:30 p.m. - 3:30 p.m.

61420601
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 10.07.2025
09:00 am - 12:00 pm

61402020
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 31.07.2025
09:00 am - 12:00 pm

61420602
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Friday, 05.09.2025
09:00 am - 12:00 pm

61420603
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 04.09.2025
09:00 am - 12:00 pm

61402021
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 02.10.2025
12:30 p.m. - 3:30 p.m.

61420604
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 02.10.2025
09:00 am - 12:00 pm

61402022
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 23.10.2025
09:00 am - 12:00 pm

61420605
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 27.11.2025
09:00 am - 12:00 pm

61424564
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 18.12.2025
09:00 am - 12:00 pm

61424565
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 18.12.2025
1:00 pm - 4:00 pm

61424566
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 12.02.2026
09:00 am - 12:00 pm

61424567
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 12.02.2026
1:00 pm - 4:00 pm

61424568
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 19.03.2026
09:00 am - 12:00 pm

61424569
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 09.04.2026
09:00 am - 12:00 pm

61424570
Module
7

Application of machine learning in projects

Once all the questions from the self-study units have been answered, the participants' practical exercise projects are evaluated. Your:e trainer will then give you an outlook on the deployment of machine learning models. 

Webinar
180 min.

Thursday, 30.04.2026
09:00 am - 12:00 pm

61424571

Course overview

Contents and course schedule

1. machine learning and data mining

  • Basics of data mining and machine learning
  • Important learning procedures explained in detail
  • Implementing data projects with CRISP-DM
  • Business Understanding: What does data say?

2. data understanding and data preparation

  • All about data types and data sources
  • Understanding data: What information does data contain?
  • First practical examples with exercises in KNIME
  • Data preparation for data projects

3. modeling and evaluation

  • Clustering with algorithms
  • Regression models
  • Classification models
  • The most important metrics
  • Practical examples in KNIME

4. an outlook on deep learning in neural networks

  • How neural networks work
  • Overview of the architectures
  • Bringing machine learning into production - an outlook
  • Excursus: Deep learning as a sub-area of machine learning

This is how you learn in this course

This online course offers you a digital blended concept that has been developed for part-time learning. With a time budget of at least 3-4 hours per week, you are sure to reach your goal. Alternatively, you can schedule the learning units flexibly. This is how you learn in the course:

Self-study phases: Learn independently, at your own pace and whenever you want. Our courses offer you didactically high-quality learning material with videos, articles, interactive exercises, quizzes and learning checks.

Live webinars: In regular online seminars, you will meet your trainers in person. You will receive answers to your questions, specific assistance and instructions on how to deepen your knowledge and apply the skills you have acquired in practical exercises.

Practical tasks: In order to learn the skills in practice, you will be given access to training sets that you can work on yourself using Python or the open software KNIME. You will clean up data, train your own models and get to know important tools. No prior knowledge is required.

Learning community: A digital learning community is available to you throughout the course. Exchange ideas with other participants and the trainers and clarify your questions.

Future Jobs Club: Get exclusive access to a business network, micro-learningssparks), news and future work hacks.

Certificate of attendance and Open Badge: As a graduate of the course, you will receive a certificate and an Open Badge that you can easily share in professional networks (e.g. LinkedIn).