Machine Learning and Deep Learning

Course overview

Machine learning and deep learning are central technologies for handling large amounts of data - from automated predictions to self-learning systems. Understanding the relationships between classical machine learning and more complex deep learning methods allows for better integration of AI projects into professional practice. This training introduces you to both areas. What you will learn Fundamental principles of machine learning: data preparation, model types, and evaluation of results Deep learning as an advancement of machine learning through neural networks Topics include, among others, image and speech recognition as well as other AI applications Prompt basics for targeted use of AI tools like ChatGPT and Claude Research with AI support, e.g., product research and preparation for conversations Basic handling of CRM systems for data protection-compliant documentation Course content The training connects machine learning and deep learning in a common context: both methods are based on learning models but differ in complexity and application areas. Additionally, the fundamentals of AI are linked with research and communication tasks, such as handling information and customer data. Your prospects The acquired foundational knowledge of machine learning and deep learning supports you in entering data-related fields, such as data analysis or AI-supported customer contact.

Upcoming dates

• 2026-09-29T22:00:00.000Z · 2027-02-16T23:00:00.000Z · Aachen · Combined Learning
• 2026-09-29T22:00:00.000Z · 2027-02-16T23:00:00.000Z · Zwickau · Combined Learning
• 2026-09-29T22:00:00.000Z · 2027-02-16T23:00:00.000Z · Zittau · Combined Learning
• 2026-09-29T22:00:00.000Z · 2027-02-16T23:00:00.000Z · Würzburg · Combined Learning
• 2026-09-29T22:00:00.000Z · 2027-02-16T23:00:00.000Z · Wuppertal · Combined Learning