In this five-day web seminar, you will receive a balanced mix of theory and practice on machine learning methods. You will learn about classical methods and also get a deep insight into neural networks. To enable you to work along with the practical exercises in between, we will start with an introduction to Python with the most important libraries in order to apply them to the methods afterwards:
- Basics of programming with Python
- Data processing with NumPy and Pandas
- Visualization of data
- Decision trees & Random Forests
- k-Nearest-Neighbors and hyperparameter optimization
- Support Vector Machines
- Regression and classification with Artificial Neural Networks
- Time Series and Convolutional Neural Networks
- Imputer methods
- Dimensionality reduction
- Clustering methods
|Detailed program as|
Duration: 5 days, 8 hours each (incl. breaks)
Plattform: BigBlueButton, you only need a browser
Number of participants: 3 – 6
Costs p. participant: 1500 € (gross),
also available as company training for a total of 5000 € (gross)
Included in the price:
- Course documents as PDFs + practical elements as code
- Certificate of attendance
Learning goals: Kick-start into the methods of machine learning. Through theory and practical application, participants get an overview of which method is suitable for which application and learn how to implement it. After the course, participants are directly able to write their first applications.
With this webinar you get everything you need to get started: an overview of the most common methods and the understanding to apply them. Maybe you already have data and are wondering how to train a model from it? That’s exactly what you’ll work through in the course with various sample data sets for regression and classification problems in concise exercises. The instructor will provide assistance with programming and will always be available to answer questions. So that the code doesn’t seem like a black box to you, the elaborately illustrated material will give you an understanding of how the algorithms and neural networks work. This will help you better decide which methods are well suited for your data.
Our courses are aimed at interested engineers, scientists and computer scientists who want to understand how the processes work and how to apply them. Basic knowledge of programming and mathematics is assumed.