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100% fundable

AI+ Architect Practitioner™

Sound AI architecture is built on structured approaches, proven methods, and a clear understanding of technical interrelationships. This course explains how AI-powered systems can be conceived, modeled, and sustainably operated.

Key topics

  • Concepts and principles for building AI-driven architectures.
  • Data modeling and workflow design in AI environments.
  • Selecting and applying appropriate AI tools for scalable systems.
  • Quality by design as the foundation of stable AI solutions.
  • Current developments in automation and generative AI.

Prerequisite
Basic IT knowledge and a fundamental understanding of data-driven working methods are recommended.

Target group
Technical specialists, IT consultants, and development teams who want to approach AI architecture in a strategic and methodically sound way.

Completing this course provides a solid foundation for designing and operating modern AI architectures – hands-on, structured, and future-oriented.

Course content
  • Getting started with the world of neural networks
  • How neural networks are structured and how they function
  • Practice: Building a basic neural network from scratch
  • Adjusting hyperparameters and understanding their impact
  • Overview of common optimization algorithms
  • Regularization techniques for stable, robust models
  • Practice: Hyperparameter tuning and optimization in action
  • Core concepts in machine-based language processing
  • Suitable network architectures for NLP tasks
  • Practice: Implementing and testing an NLP model
  • Core concepts in machine-based image recognition
  • Appropriate network architectures for computer vision tasks
  • Practice: Developing and building a computer vision model
  • Methods and metrics for assessing model performance
  • Strategies for targeted performance improvement
  • Practice: Evaluating and optimizing an AI model
  • Understanding infrastructure requirements for AI projects
  • Deployment strategies for AI systems
  • Practice: Deploying an AI model in a real-world scenario
  • Ethical principles and key questions in AI development
  • Guidelines for responsible AI design in practice
  • Practice: Analyzing ethical dimensions of real-world AI systems
  • What generative AI models can do and how they are built
  • Use cases for generative AI across different industries and domains
  • Practice: Working hands-on with generative AI models
  • Discovering current methods and trends from AI research
  • Advanced design approaches for modern AI systems
  • Practice: Analyzing and reviewing current AI research papers
  • Presenting and reflecting on the final project
  • Course review and outlook on next steps
  • Practice: Developing and completing your own capstone project
  • How AI agents are structured and what they can do
  • Real-world case studies and application examples
  • Practical exercises with AI agents

Up to 100% funding for your continuing education

Attractive funding opportunities are available for numerous continuing education programs – depending on the funding program, up to 100% funding is possible.
The requirement is that you live or work in Germany. Our funding opportunities are not available outside of Germany.

Funding opportunities are available for career starters, job seekers, career changers, startups, experienced professionals, those seeking career advancement, and specialists.

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