Machine Learning Developer with Reinforcement Learning

Course overview

This course initially presents the central tasks of machine learning development. In the first step, 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 use algorithms to find independent solutions to problems. In the final step of machine learning development, the course delves into a subfield of machine learning with deep learning, explaining its methods based on neural networks. Additionally, you will expand your knowledge of reinforcement learning, one of the three main techniques of machine learning, where software is trained through direct interaction with its environment in the form of trial and error to achieve optimal results.

Upcoming dates

• 2026-09-20T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Berlin · Combined Learning
• 2026-09-20T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Berlin · Combined Learning
• 2026-09-20T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Aachen · Combined Learning
• 2026-09-20T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Augsburg, Bayern · Combined Learning
• 2026-09-20T22:00:00.000Z · 2027-01-14T23:00:00.000Z · Bielefeld · Combined Learning