Digital Transformation with IoT and Edge Computing Training Course

This instructor-led, live training in Norway (online or onsite) is designed for business leaders who want to drive Digital Transformation within their organizations.

Upon completing this training, participants will be able to:

• Explain the core concepts of Digital Transformation
• Identify organizational areas where digitization is most beneficial
• Develop a digitization strategy that outlines the necessary changes in processes, technology, and training.

This instructor-led, live training in Norway (online or onsite) is aimed at intermediate-level to advanced-level IT leaders, compliance officers, and digital transformation managers who wish to use a structured roadmap approach to implement digital sovereignty initiatives.

By the end of this training, participants will be able to assess their organization's digital sovereignty maturity, develop a comprehensive strategy, create an actionable implementation roadmap, and establish governance frameworks.

This instructor-led, live training in Norway (online or onsite) is aimed at intermediate-level developers, system architects, and industry professionals who wish to leverage Edge AI for enhancing IoT applications with intelligent data processing and analytics capabilities.

By the end of this training, participants will be able to:

• Understand the fundamentals of Edge AI and its application in IoT.
• Set up and configure Edge AI environments for IoT devices.
• Develop and deploy AI models on edge devices for IoT applications.
• Implement real-time data processing and decision-making in IoT systems.
• Integrate Edge AI with various IoT protocols and platforms.
• Address ethical considerations and best practices in Edge AI for IoT.

This instructor-led, live training in Norway (online or onsite) is designed for product managers and developers seeking to decentralize data management for improved performance, by leveraging smart devices located on the source network.

Upon completion of this training, participants will be equipped to:

• Grasp the fundamental concepts and benefits of Edge Computing.
• Recognize practical use cases and real-world examples of Edge Computing applications.
• Design and implement Edge Computing solutions to accelerate data processing and lower operational costs.

This instructor-led, live training in Norway (online or onsite) is aimed at intermediate-level professionals who wish to apply Federated Learning to optimize IoT and edge computing solutions.

By the end of this training, participants will be able to:

• Understand the principles and benefits of Federated Learning in IoT and edge computing.
• Implement Federated Learning models on IoT devices for decentralized AI processing.
• Reduce latency and improve real-time decision-making in edge computing environments.
• Address challenges related to data privacy and network constraints in IoT systems.

This instructor-led, live training in Norway (online or onsite) is designed for digital technology professionals at the beginner level who wish to gain comprehensive knowledge and practical tools for understanding and acting on responsible digital practices.

Upon completing this training, participants will be able to:

• Comprehend the environmental, social, and broader societal impacts of digital technology.
• Master best practices for reducing digital footprints in both professional and personal contexts.
• Gain insight into eco-design principles for sustainable digital services.
• Apply responsible digital practices within their professional roles.

This instructor-led, live training in Norway (online or onsite) is aimed at beginner-level security professionals who wish to gain the knowledge and skills necessary to adapt to the rapidly evolving digital landscape in the security industry.

By the end of this training, participants will be able to:

• Understand digital transformation within the context of security.
• Discover how digital solutions can enhance security operations, efficiency, and effectiveness.
• Manage security-related data to support informed decision-making.