Artificial Intelligence - Development

Course overview

Goals of the Training The focus of the training in Artificial Intelligence - Development is on understanding and applying Artificial Intelligence (AI) and its various facets. The course covers fundamental concepts of Artificial Intelligence (AI) and deepens knowledge in the area of Machine Learning, both in Supervised and Unsupervised Learning. Another emphasis is on Feature Engineering, which encompasses data preparation and analysis. Neural networks and Deep Learning are also addressed to provide a general picture of modern AI development. The training connects the theoretical content of the individual subject areas and offers insights into the technologies that shape the future of AI. The course is designed to create a general understanding of the mechanisms and methods of Artificial Intelligence. Contents of the Training Artificial Intelligence History of AI Modern AI Systems Reinforcement Learning Natural Language Processing (NLP) Computer Vision Machine Learning - Supervised Learning Introduction to Machine Learning Regression Basic Classification Techniques Support Vector Machines Decision Trees and Regression Trees Machine Learning - Unsupervised Learning and Feature Engineering Introduction to Unsupervised Learning and Feature Engineering Clustering Dimensionality Reduction Feature Engineering Feature Selection Automated Feature Generation Neural Networks and Deep Learning Introduction to Neural Networks Feed-Forward Networks Avoiding Overfitting Convolutional Networks Recurrent Neural Networks Transformer Architecture

Upcoming dates

• 2026-10-07T22:00:00.000Z · 2027-02-07T23:00:00.000Z · Karlsruhe, Baden · Blended Learning
• 2026-10-07T22:00:00.000Z · 2027-02-07T23:00:00.000Z · Duisburg · Blended Learning
• 2026-10-07T22:00:00.000Z · 2027-06-07T22:00:00.000Z · Duisburg · Blended Learning
• 2026-10-07T22:00:00.000Z · 2027-06-07T22:00:00.000Z · Nürnberg, Mittelfranken · Blended Learning
• 2026-10-07T22:00:00.000Z · 2027-02-07T23:00:00.000Z · Mannheim · Blended Learning