Weiterbildung AI

Weiterbildung AI

practical advanced training courses for machine learning and artificial intelligence

AI and Machine Learning

Machine Learning Inhouse-Training Webinar Data Science Neural Networks TensorFlow Keras Scikit-Learn Python Time Series Deep Learning Exercises Outlier Detection Artificial Intelligence Practical Elements Data Analysis Smartfactory Predictive Maintenance Ensemble Learning Matplotlib Seaborn Imputer Lazy-Learning Support Vector Machines Education Clustering Convolutional Neural Networks Feature Engineering Decision Trees Principal Component Analysis Auto-Encoder Data Mining Visualization Plotting Correlation Transformation Dimensionality Reduction Pre-Processing Cross Validation Training Modeling Heatmap Data Programming Robotics Feature Space Industry 4.0 Digital Health Class Activation Maps Regression Accuracy Mean Absolute Error Classification Estimator Prediction Encoding Supervised Learning Unsupervised Learning Reinforcement Learning Mean Squared Error Fully Connected DBSCAN CART Loss Optimization Regularization Overfitting Random Forest SVM PCA k-NN NumPy AI Pandas ANN CNN Recurrent Neural Networks RNN

Machine learning is becoming increasingly important in today’s world. Time and again, there are innovations that are only possible with methods from the field of artificial intelligence and machine learning. The fields of application are very diverse:

  • Industry 4.0 / Smartfactory
  • Logistics und Supply Chain Management
  • Predictive Maintenance
  • Customer analysis

You too can benefit from the new possibilities of modeling data.

We offers webinars on machine learning as part of WeAI, as well as Inhouse training at your company. You will get an introduction to Python and learn about the relevant methods from decision trees to Convolutional Neural Networks.

Machine learning is not new, but the pace of development is rapid. For many applications, however, classic machine learning methods are often better suited. Learn about the relevant methods and what fits best to your applications.

Our courses are very practical. We teach the algorithms and models both in theory, but also in practice with the free programming language Python. Python is easy to learn and all relevant frameworks are available in Python. So after the practical elements in the course, you can jump right in and start modeling your own data.

Deep Learning offers the opportunity to tackle tasks that were unthinkable a few years ago. Learn about different types of neural networks for different tasks – from time series to image processing.

You want to find unusual behavior in data? With us, you will learn unsupervised learning techniques that will help you group your data and find outliers. If your data has many properties or features, we will show you how to compress the feature space to get meaningful groupings.