Machine Learning Developer

Course overview

This course introduces the central tasks of machine learning development. Initially, data analysis and visualization, as well as data management, are explained in detail and placed in the context of Big Data. The next step takes you from the fundamentals of machine learning to the two categories of supervised and unsupervised learning, providing insight into evaluation and improvement. It demonstrates how IT systems can identify patterns in existing data sets and find independent solutions to problems using algorithms. Finally, the course delves into a subfield of machine learning with deep learning, explaining its methods based on neural networks. Data Analytics Introduction to Data Analysis Review of Python Basics Data Analysis, Data Analytics Artificial Intelligence (AI) in the Work Process Data Visualization Data Management Data Analysis in the Big Data Context Dashboards Text Mining Project Work in Data Analytics Machine Learning Introduction to Machine Learning Supervised Learning Unsupervised Learning Evaluation and Improvement Project Work in Machine Learning Deep Learning Machine Learning: Deep Learning Basics of Neural Networks Convolutional Neural Network (CNN) Transfer Learning Regional CNN Methods of Creative Image Generation Recurrent Neural Networks Text Processing with Neural Networks Language Models Deep Reinforcement Learning Bayesian Neural Networks Project Work in Deep Learning Changes are possible; course content is regularly updated.

Upcoming dates

• 2026-08-02T22:00:00.000Z · 2026-10-22T22:00:00.000Z · Karlsruhe, Baden · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-10-22T22:00:00.000Z · Albstadt, Württemberg · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-10-22T22:00:00.000Z · Aachen · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-10-22T22:00:00.000Z · Alzenau in Unterfranken · Combined Learning
• 2026-08-02T22:00:00.000Z · 2026-10-22T22:00:00.000Z · Augsburg, Bayern · Combined Learning