intellcert Academy · Artificial Intelligence
AI for Time Series Data: Analysis, Forecasting and Anomaly Detection
Participants will be able to: Analyze and structure time-series data and identify common patterns (trend, seasonality, anomalies) Apply AI models for forecasting and anomaly detection.
Overview
Course contents
Our professional training courses are designed for professionals, specialists, and experts who wish to expand their knowledge in a targeted way.
Hands-on exercises
- Building a simple forecasting model for industrial time-series data
- Developing an anomaly detection system based on sensor data
- Analysis of a predictive maintenance use case
- Comparison of classical vs. machine learning-based time-series methods
Learning objectives
- analyze and prepare time series data in a structured way and recognize typical patterns (trend, seasonality, disturbances)
- apply AI models for forecasting and anomaly detection
- technically implement or evaluate predictive maintenance use cases
- select suitable modeling approaches for time series problems
- assess the limitations of time series AI systems in real-world environments
- understand industrial AI applications in the area of monitoring and forecasting
Target audience
- Data scientists and data analysts
- Industrial engineers and automation technicians
- AI developers with a focus on industrial applications
- Specialists from production, energy, logistics and IoT
- Predictive maintenance and condition monitoring teams
- Participants from IC-805-E-04 and IC-805-E-06
Prerequisites
- Required:
- Comparable knowledge in data analysis and machine learning
- Recommended:
- Basic knowledge of statistics and Python-based data analysis
- Not suitable for complete AI beginners without data or programming experience.
Required
- IC-805-E-04. Developing and Integrating AI Systems, or
- IC-805-E-06. MLOps & AI Operations (for production deployment context)
Certification requirement
Without certification option
Delivery format: Online. For on-site or in-house training, please send us a request via our contact form. We will get in touch with you shortly thereafter.
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Flexible scheduling is available for this service. Please contact us to arrange a convenient date.
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