Time Series Analysis and Classification for Machine Learning Engineer

Course overview

Time series analysis and classification are among the frequently used methods in the machine learning field. Both areas present specific requirements for data, models, and evaluation. A structured approach is the foundation for reliable results. !Course Content !1. Fundamentals of Time Series Analysis *Characteristics of time-dependent data *Preparation and preprocessing *Typical problem statements !2. Methods for Time Series Modeling *Statistical and ML-based approaches *Incorporation of seasonal effects *Assessment of forecast quality !3. Fundamentals of Classification Tasks *Distinction between different task types *Selection of suitable algorithms *Handling imbalanced classes !4. Evaluation and Application of Models *Metrics for model evaluation *Validation strategies *Integration into applications !Professional Relevance *Informed selection of appropriate methods *Reliable basis for data-driven decisions *Structured development of own ML solutions

Upcoming dates

• 2026-07-31T22:00:00.000Z · 2026-08-31T22:00:00.000Z · Hamburg · Combined Learning
• 2026-09-07T22:00:00.000Z · 2026-11-23T23:00:00.000Z · Hamburg · Combined Learning
• 2026-09-07T22:00:00.000Z · 2027-02-09T23:00:00.000Z · Hamburg · Combined Learning
• 2026-09-07T22:00:00.000Z · 2026-11-23T23:00:00.000Z · Bremen · Combined Learning
• 2026-09-07T22:00:00.000Z · 2027-02-09T23:00:00.000Z · Bremen · Combined Learning