AI Strategy: Implementation of AI Solutions

Course overview

This course provides strategic approaches for the successful implementation of AI solutions in business processes. Automated data pipelines for the implementation of AI solutions in Artificial Intelligence Clean, harmonize, and optimize data sources for machine learning algorithms Develop efficient workflows to seamlessly integrate AI models into existing systems Utilize automation techniques to make data-driven AI processes scalable and efficient SQL for structured data processing in Artificial Intelligence Apply joins and aggregations to optimally adjust training and validation data Write optimized queries to supply AI models with high-quality data Optimize database management to support AI applications with precise and up-to-date data Interactive analysis and model evaluation with Power BI Create dynamic dashboards to clearly present model metrics and AI results Utilize DAX functions to optimize data-driven calculations for model evaluation Develop meaningful reports to facilitate data-based decisions in AI implementation Neural networks and machine learning for AI solutions Recognize patterns in data to specifically optimize AI models for business and research processes Employ Convolutional and Recurrent Neural Networks for image recognition and speech processing Utilize hyperparameter tuning and transfer learning to develop robust and powerful AI models

Upcoming dates

• 2026-10-11T22:00:00.000Z · 2027-06-21T22:00:00.000Z · Berlin · Hybrid Learning
• 2026-10-11T22:00:00.000Z · 2028-03-01T23:00:00.000Z · Berlin · Hybrid Learning
• 2026-10-11T22:00:00.000Z · 2027-06-21T22:00:00.000Z · München · Hybrid Learning
• 2026-10-11T22:00:00.000Z · 2028-03-01T23:00:00.000Z · München · Hybrid Learning
• 2026-10-11T22:00:00.000Z · 2027-06-21T22:00:00.000Z · Berlin · Hybrid Learning