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. In the next step, the course takes you from the fundamentals of machine learning to the two categories of supervised and unsupervised learning and provides 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 and explains 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 Data Analytics Machine Learning Introduction to Machine Learning Supervised Learning Unsupervised Learning Evaluation and Improvement Project Work 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 Deep Learning Changes are possible; course content is regularly updated.

Upcoming dates

• 2026-10-18T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Aachen · Combined Learning
• 2026-10-18T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Augsburg, Bayern · Combined Learning
• 2026-10-18T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Berlin · Combined Learning
• 2026-10-18T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Berlin · Combined Learning
• 2026-10-18T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Bochum · Combined Learning