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100% fundable

AI+ Robotics Practitioner™

Smart machines, adaptive systems, and autonomous control are changing how companies produce and make decisions. Understanding how AI and robotics work together enables more targeted process automation and faster innovation. This training delivers exactly that understanding – structured, hands-on, and directly applicable.

Key topics

  • Understand the connection between artificial intelligence and robotics.
  • Learn about autonomous systems and intelligent control approaches.
  • Understand the role of sensors, data processing, and machine perception.
  • Examine adaptive robotics in industrial and service-oriented applications.
  • Consider safety aspects, responsibility, and regulatory requirements.

Prerequisite
Basic technical knowledge or practical experience in digital work environments is sufficient – specific prior knowledge in robotics is not required.

Target group
Developers, IT professionals, engineers, and managers from production, research, and transformation who want to understand and apply AI-based robotics solutions.

Intelligent machines are among the defining technologies of the coming years. Mastering the connection between AI and robotics positions you as an important driver of industrial and societal transformation.
 

course content
  • Robotics at a glance: history, development, and societal impact
  • How AI is transforming modern robotics
  • Fundamentals of machine learning and deep learning in a robotics context
  • The role of neural networks in intelligent systems
  • Understanding the components of intelligent systems where AI meets robotics
  • Sensors, actuators, and control systems in detail
  • Exploring and contextualizing machine learning algorithms in robotics
  • Foundations and structure of autonomous systems
  • Learn about the key components of intelligent agent systems
  • Analyze real-world examples of autonomous vehicles and industrial robotics
  • ROS (Robot Operating System) as a development platform
  • Using Python effectively for robotics and machine learning
  • TensorFlow and PyTorch in an AI robotics context
  • Getting to know and comparing other relevant frameworks
  • Understanding neural networks and CNNs in action
  • Robotic image processing systems: object recognition and identification
  • Exercise: training a CNN for object recognition
  • Application example: Image processing for precise robot-assisted manufacturing processes
  • Understanding the core principles of reinforcement learning
  • Implementing RL algorithms for robotics
  • Exercise: developing RL models for autonomous robots
  • Use case: optimizing warehouse workflows with reinforcement learning
  • Generative AI and GANs at a glance
  • Creative robots: design and innovation with AI
  • Exercise: generating novel designs for robotics applications
  • Use case: customized manufacturing with generative AI
  • Foundations of natural language processing for robotics
  • Building voice-controlled control systems
  • Exercise: developing a voice command robot interface
  • Case study: Examining assistive robotics in healthcare
  • Application Assignment 1: Developing an AI model for object recognition using Python
  • Application Assignment 2: Implementing route planning, obstacle detection, and localization using Python
  • Application Assignment 3: Implementing a PID controller using Python
  • Exploring real-world examples from precision agriculture and automated manufacturing processes
  • Blockchain technology in combination with robotics
  • Quantum computing and its potential for intelligent systems
  • Understanding RPA fundamentals and deployment scenarios
  • Getting to know relevant RPA tools and how they work
  • Integrating AI purposefully into RPA processes
  • Considering ethical aspects in the use of AI and robotics
  • Knowing safety standards for AI-controlled robots
  • Understanding and applying AI guidelines and regulatory frameworks
  • Current innovations in robotics and AI at a glance
  • Contextualizing the impact of AI and robotics on work and society
  • Clarifying the concept and definition of AI agents
  • Key capabilities of AI agents in robotics applications
  • Application areas and trends for AI agents in robotics
  • How an AI agent works – explained
  • Core features of autonomous AI systems
  • Future perspectives for AI agents in robotics
  • Agent types and their specific properties

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.