UX Optimization with AI

Course overview

Course Objective The course 'UX Optimization with AI' addresses methods of user-centered design in the field of UX design and connects these with machine learning techniques. The goal is to convey approaches for data-driven analysis of user interactions and to derive user-related adjustments for digital products. Content The training 'UX Optimization with AI' covers the collection and evaluation of usage data, including clickstream analysis, heatmaps, and session replays, to identify usage patterns. Following this, the application of AI-supported tools for prototyping, text and image generation, as well as support for information architecture and microcopy will be discussed. Another focus is on testing methods such as A/B testing, multivariate testing, and usability testing with AI-supported evaluation. Finally, interpretation of key figures, reporting structures, and ethical aspects such as data protection, bias detection, and traceability of models will be addressed. Keywords such as conversion tracking, prompt engineering, accessibility, and interaction design are embedded within the course. Learning Objectives - Analyze user flows based on metrics such as bounce rate, dwell time, and task completion rate - Apply AI-supported tools for creating low- and high-fidelity prototypes, including microcopy - Implement A/B tests and integrate the results into iterative UX decisions Career Prospects The course content is applicable in fields such as UX designers with a focus on data analysis and test planning. Typical areas of activity include UX research using AI-supported evaluations and reporting. The course addresses content for roles such as conversion managers focusing on experiment design and product managers responsible for user-related metrics and backlog prioritization. Summary The course 'UX Optimization with AI' addresses the connection between UX methodology and AI-supported analysis and design processes. Within this training, data evaluation, prototyping, and testing methods for digital products are discussed. The conveyed focuses are aimed at fields such as UX design, UX research, conversion management, and product management.

Upcoming dates

• 2026-10-04T22:00:00.000Z · 2026-12-28T23:00:00.000Z · Leipzig · Combined Learning
• 2026-10-04T22:00:00.000Z · 2026-11-15T23:00:00.000Z · Leipzig · Combined Learning
• 2026-11-01T23:00:00.000Z · 2027-01-25T23:00:00.000Z · Leipzig · Combined Learning
• 2026-11-01T23:00:00.000Z · 2026-12-13T23:00:00.000Z · Leipzig · Combined Learning