Booking no:
36136
Develop a deep technical understanding of the concepts behind artificial intelligence. In this course, you will learn how data mining, data models and algorithms really work and implement practical projects yourself. After participating, you will be able to understand machine learning processes in detail, make informed decisions and explore technical issues in depth.
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.
Thursday, 09.01.2025
09:00 am - 11:00 am
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.
Thursday, 12.06.2025
1:00 pm - 3:00 pm
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.
Thursday, 23.01.2025
09:00 am - 12:00 pm
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.
Thursday, 26.06.2025
09:00 am - 12:00 pm
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.
Thursday, 06.02.2025
09:00 am - 12:00 pm
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.
Thursday, 10.07.2025
09:00 am - 12:00 pm
1. machine learning and data mining
2. data understanding and data preparation
3. modeling and evaluation
4. an outlook on deep learning in neural networks
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).
