Booking no:
36405
Learn how to master the first steps in data analysis and implement complete data processes with the help of the KNIME tool. Among other things, you will learn how to use algorithms to evaluate data and visualize the results of your data analyses.
The first webinar starts with a detailed presentation of the structure and objectives of the course. Together, we will also take a look at the first learning units and discuss personal expectations.
Monday, 23.06.2025
11:00 a.m. - 12:00 p.m.
The first webinar starts with a detailed presentation of the structure and objectives of the course. Together, we will also take a look at the first learning units and discuss personal expectations.
Monday, 01.09.2025
11:00 a.m. - 12:00 p.m.
The first webinar starts with a detailed presentation of the structure and objectives of the course. Together, we will also take a look at the first learning units and discuss personal expectations.
Monday, 10.11.2025
09:00 am - 10:00 am
The first webinar starts with a detailed presentation of the structure and objectives of the course. Together, we will also take a look at the first learning units and discuss personal expectations.
Monday, 23.02.2026
09:00 am - 10:00 am
Part 1: Business understanding and concepts of data mining
At the beginning of the first self-study unit, you will learn to identify use cases and describe how you can solve business problems by analyzing data and applying machine learning. You will then learn all about the basics and requirements for your own data projects and dive deep into the concepts of data structures and machine learning:
Part 2: Installation and introduction to working with KNIME
After you have learned all about the basics and concepts of data science, the next step is to take your first steps in practical application. You will familiarize yourself with the use of the KNIME tool, a powerful development platform for data mining, with which you can carry out complex data analysis and data science projects:
Part 1: Business understanding and concepts of data mining
At the beginning of the first self-study unit, you will learn to identify use cases and describe how you can solve business problems by analyzing data and applying machine learning. You will then learn all about the basics and requirements for your own data projects and dive deep into the concepts of data structures and machine learning:
Part 2: Installation and introduction to working with KNIME
After you have learned all about the basics and concepts of data science, the next step is to take your first steps in practical application. You will familiarize yourself with the use of the KNIME tool, a powerful development platform for data mining, with which you can carry out complex data analysis and data science projects:
Part 1: Business understanding and concepts of data mining
At the beginning of the first self-study unit, you will learn to identify use cases and describe how you can solve business problems by analyzing data and applying machine learning. You will then learn all about the basics and requirements for your own data projects and dive deep into the concepts of data structures and machine learning:
Part 2: Installation and introduction to working with KNIME
After you have learned all about the basics and concepts of data science, the next step is to take your first steps in practical application. You will familiarize yourself with the use of the KNIME tool, a powerful development platform for data mining, with which you can carry out complex data analysis and data science projects:
Part 1: Business understanding and concepts of data mining
At the beginning of the first self-study unit, you will learn to identify use cases and describe how you can solve business problems by analyzing data and applying machine learning. You will then learn all about the basics and requirements for your own data projects and dive deep into the concepts of data structures and machine learning:
Part 2: Installation and introduction to working with KNIME
After you have learned all about the basics and concepts of data science, the next step is to take your first steps in practical application. You will familiarize yourself with the use of the KNIME tool, a powerful development platform for data mining, with which you can carry out complex data analysis and data science projects:
In the second webinar, you will review the content of the first self-study phase together with the trainers .
Monday, 04.08.2025
1:00 pm - 2:00 pm
In the second webinar, you will review the content of the first self-study phase together with the trainers .
Monday, 06.10.2025
11:00 a.m. - 12:00 p.m.
In the second webinar, you will review the content of the first self-study phase together with the trainers .
Monday, 15.12.2025
09:00 am - 10:00 am
In the second webinar, you will review the content of the first self-study phase together with the trainers .
Monday, 30.03.2026
09:00 am - 10:00 am
In this module, you will learn all the steps and concepts for preparing the data for the modeling process. First, you will analyse the data by applying different visualization techniques to identify patterns, trends and outliers. You will then clean the data and prepare it for transformation:
In this module, you will learn all the steps and concepts for preparing the data for the modeling process. First, you will analyse the data by applying different visualization techniques to identify patterns, trends and outliers. You will then clean the data and prepare it for transformation:
In this module, you will learn all the steps and concepts for preparing the data for the modeling process. First, you will analyse the data by applying different visualization techniques to identify patterns, trends and outliers. You will then clean the data and prepare it for transformation:
In this module, you will learn all the steps and concepts for preparing the data for the modeling process. First, you will analyse the data by applying different visualization techniques to identify patterns, trends and outliers. You will then clean the data and prepare it for transformation:
In the third webinar, you will focus on the exercise project together with the speaker. A possible solution will be presented. Of course, there will also be ample opportunity to ask questions.
Monday, 15.09.2025
1:00 pm - 2:00 pm
In the third webinar, you will focus on the exercise project together with the speaker. A possible solution will be presented. Of course, there will also be ample opportunity to ask questions.
Monday, 17.11.2025
11:00 a.m. - 12:00 p.m.
In the third webinar, you will focus on the exercise project together with the speaker. A possible solution will be presented. Of course, there will also be ample opportunity to ask questions.
Monday, 26.01.2026
09:00 am - 10:00 am
In the third webinar, you will focus on the exercise project together with the speaker. A possible solution will be presented. Of course, there will also be ample opportunity to ask questions.
Monday, 11.05.2026
09:00 am - 10:00 am
Now it's time for modeling based on the data. You will first learn how to find the right algorithm and methodology to achieve optimal results. You will then focus on how to adequately evaluate and interpret the results of the models. In practical exercises, you will carry out the processes yourself in KNIME and also implement more complex classification and clustering tasks:
Now it's time for modeling based on the data. You will first learn how to find the right algorithm and methodology to achieve optimal results. You will then focus on how to adequately evaluate and interpret the results of the models. In practical exercises, you will carry out the processes yourself in KNIME and also implement more complex classification and clustering tasks:
Now it's time for modeling based on the data. You will first learn how to find the right algorithm and methodology to achieve optimal results. You will then focus on how to adequately evaluate and interpret the results of the models. In practical exercises, you will carry out the processes yourself in KNIME and also implement more complex classification and clustering tasks:
Now it's time for modeling based on the data. You will first learn how to find the right algorithm and methodology to achieve optimal results. You will then focus on how to adequately evaluate and interpret the results of the models. In practical exercises, you will carry out the processes yourself in KNIME and also implement more complex classification and clustering tasks:
You will use the fourth webinar for another deep dive into modeling concepts. You will review the most important facts about algorithms and methodologies and focus in particular on evaluating the results of the models used.
Monday, 03.11.2025
11:00 a.m. - 12:00 p.m.
You will use the fourth webinar for another deep dive into modeling concepts. You will review the most important facts about algorithms and methodologies and focus in particular on evaluating the results of the models used.
Monday, 12.01.2026
11:00 a.m. - 12:00 p.m.
You will use the fourth webinar for another deep dive into modeling concepts. You will review the most important facts about algorithms and methodologies and focus in particular on evaluating the results of the models used.
Monday, 16.03.2026
09:00 am - 10:00 am
You will use the fourth webinar for another deep dive into modeling concepts. You will review the most important facts about algorithms and methodologies and focus in particular on evaluating the results of the models used.
Monday, 06.07.2026
09:00 am - 10:00 am
The fourth self-learning phase deals with the final steps in the CRISP-DM process, the evaluation and deployment of the data model. Here, too, you will proceed step by step using instructions and your own practical tasks in KNIME. At the end, you will put the entire process into production and transfer it to an automated KNIME workflow:
The fourth self-learning phase deals with the final steps in the CRISP-DM process, the evaluation and deployment of the data model. Here, too, you will proceed step by step using instructions and your own practical tasks in KNIME. At the end, you will put the entire process into production and transfer it to an automated KNIME workflow:
The fourth self-learning phase deals with the final steps in the CRISP-DM process, the evaluation and deployment of the data model. Here, too, you will proceed step by step using instructions and your own practical tasks in KNIME. At the end, you will put the entire process into production and transfer it to an automated KNIME workflow:
The fourth self-learning phase deals with the final steps in the CRISP-DM process, the evaluation and deployment of the data model. Here, too, you will proceed step by step using instructions and your own practical tasks in KNIME. At the end, you will put the entire process into production and transfer it to an automated KNIME workflow:
In the final webinar, you will focus on the exercise project from Module 8. In addition to insights for solutions to the task, you will also receive tips and advice from the instructor on how to prepare for the final exam.
Monday, 15.12.2025
11:00 a.m. - 12:00 p.m.
In the final webinar, you will focus on the exercise project from Module 8. In addition to insights for solutions to the task, you will also receive tips and advice from the instructor on how to prepare for the final exam.
Monday, 23.02.2026
11:00 a.m. - 12:00 p.m.
In the final webinar, you will focus on the exercise project from Module 8. In addition to insights for solutions to the task, you will also receive tips and advice from the instructor on how to prepare for the final exam.
Monday, 04.05.2026
09:00 am - 10:00 am
In the final webinar, you will focus on the exercise project from Module 8. In addition to insights for solutions to the task, you will also receive tips and advice from the instructor on how to prepare for the final exam.
Monday, 24.08.2026
09:00 am - 10:00 am
1. business understanding for data analysis
2. operation and first steps in KNIME
3. data understanding and data preparation
4. data modeling
5. deployment, monitoring and troubleshooting
6. final project
After the practical tasks, with which various scenarios and the individual stages of the CRIPS-DM process are practiced, there is a final project at the end of the course in which the entire data analysis process is run through.
This online course offers you a digital blended concept that has been specially 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 assignments: To learn the skills in practice, you will be given access to data projects that allow you to apply the techniques and methods you have learned to real-world problems. Through these exercises, you will gain a deep understanding of working with data and develop methods and techniques that you can apply in your everyday work.
Learning community: A digital learning community is available to you throughout the course. Exchange ideas with other participants and the trainers and ask questions.
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).
Future Jobs Club: Get exclusive access to a business network, micro-learningssparks), news and future work hacks.
In your online learning environment, you will find useful information, downloads and extra services for this training course once you have registered.