Multimodal AI Training in Copenhagen

This live, instructor-led training in Copenhagen (online or onsite) is designed for intermediate to advanced AI professionals, including researchers, developers, and data scientists, who aim to utilize DeepSeek’s multimodal features for cross-modal learning, AI automation, and advanced decision-making.

Upon completion, participants will be able to:

• Implement DeepSeek’s multimodal AI for text, image, and audio tasks.
• Create AI solutions that combine various data types for enhanced insights.
• Optimize and fine-tune DeepSeek models for cross-modal learning.
• Apply multimodal AI techniques to practical industry use cases.

This instructor-led live training in Copenhagen (available online or on-site) caters to intermediate and advanced AI developers, researchers, and multimedia engineers looking to build AI agents proficient in understanding and generating multi-modal content.

By the conclusion of this training, participants will be prepared to:

• Create AI agents that handle and synthesize text, image, and speech data.
• Apply multi-modal models like GPT-4 Vision and Whisper ASR.
• Improve multi-modal AI pipelines for better performance and accuracy.
• Launch multi-modal AI agents in practical, real-world settings.

This instructor-led, live training in Copenhagen (available online or onsite) is tailored for advanced AI professionals looking to refine their prompt engineering skills for multimodal AI applications.

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

• Understand the fundamentals of multimodal AI and its practical uses.
• Design and optimize prompts for generating text, images, audio, and video.
• Utilize APIs for multimodal AI platforms such as GPT-4, Gemini, and DeepSeek-Vision.
• Develop AI-driven workflows that integrate multiple content formats.

This live training in Copenhagen (online or onsite) is tailored for advanced AI developers, machine learning engineers, and researchers aiming to construct custom multimodal AI models using open-source frameworks.

By the end of the session, participants will be able to:

• Comprehend the basics of multimodal learning and data fusion.
• Develop multimodal models using DeepSeek, OpenAI, Hugging Face, and PyTorch.
• Fine-tune and optimize models for integrating text, image, and audio.
• Implement multimodal AI models in live applications.

This live, instructor-led training in Copenhagen (online or onsite) targets industrial engineers, automation specialists, and AI developers at intermediate to advanced levels who aim to apply multimodal AI to quality control, predictive maintenance, and robotics in smart factories.

Once completed, participants will have the capability to:

• Comprehend the function of multimodal AI in industrial automation.
• Integrate sensor data, image recognition, and real-time monitoring for smart factories.
• Deploy predictive maintenance via AI-driven data analysis.
• Leverage computer vision for defect detection and quality assurance.

Targeted at intermediate-level linguists, AI researchers, software engineers, and business professionals, this instructor-led, live training in Copenhagen (online or onsite) demonstrates how to utilize multimodal AI for real-time translation and language comprehension.

Upon completion, participants will be equipped to:

• Understand the core principles of multimodal AI in language processing.
• Apply AI models to translate speech, text, and visual content.
• Deploy real-time translation using AI-enabled APIs and frameworks.
• Integrate AI-driven translation into business systems.
• Assess the ethical implications of AI-powered language processing.

This live, instructor-led training, available either online or onsite in Copenhagen, is tailored for product designers, software engineers, and customer support professionals ranging from beginner to intermediate levels who aim to integrate multimodal AI into virtual assistants.

By the conclusion of this program, participants will have the capability to:

• Comprehend how multimodal AI enhances the functionality of virtual assistants.
• Integrate speech, text, and image processing within AI-powered assistant frameworks.
• Construct interactive conversational agents featuring voice and vision capabilities.
• Leverage APIs for speech recognition, NLP, and computer vision.
• Implement AI-driven automation to optimize customer support and user engagement.

This live, instructor-led training session Copenhagen (delivered online or onsite) targets intermediate to advanced healthcare professionals, medical researchers, and AI developers seeking to leverage multimodal AI in medical diagnostics and healthcare applications.

By the conclusion of the program, participants will be equipped to:

• Understand the pivotal role of multimodal AI in modern healthcare.
• Integrate both structured and unstructured medical data to support AI-driven diagnostics.
• Apply AI techniques to examine medical images and electronic health records.
• Build predictive models for diagnosing diseases and suggesting treatments.
• Utilize speech and natural language processing (NLP) for medical transcription and enhancing patient interaction.

This live training in Copenhagen empowers practitioners to design, construct, and optimize multimodal LLM workflows in Vertex AI. The curriculum explores Gemini models, long-context reasoning, and pipelines that integrate text, audio, and image data. Through hands-on labs, participants gain practical readiness for real-world implementations.

This instructor-led live training, offered in Copenhagen (online or onsite), is designed for intermediate-level finance professionals, data analysts, risk managers, and AI engineers looking to apply multimodal AI for risk analysis and fraud detection.

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

• Grasp the practical applications of multimodal AI in financial risk management.
• Interpret both structured and unstructured financial data to uncover fraud.
• Build AI models capable of detecting anomalies and irregular activities.
• Utilize NLP and computer vision technologies for the analysis of financial documents.
• Integrate AI-driven fraud detection solutions into operational financial systems.

Aimed at beginner to intermediate-level UI/UX designers, product managers, and AI researchers, this instructor-led live training in Copenhagen (online or onsite) explores how to enhance user experiences using multimodal, AI-powered interfaces.

By the conclusion of this course, participants will have the ability to:

• Comprehend the essentials of multimodal AI and its effect on human-computer interaction.
• Create and prototype multimodal interfaces leveraging AI-driven input methods.
• Utilize speech recognition, gesture control, and eye-tracking technologies.
• Evaluate the usability and performance of multimodal systems.

This live, instructor-led training in Copenhagen (available online or on-site) caters to intermediate-level creators, digital artists, and media professionals looking to apply multimodal AI to diverse content creation tasks.

By the end of the session, learners will be able to:

• Utilize AI tools to enhance music and video production processes.
• Generate original visual art and design elements with AI.
• Build interactive multimedia experiences.
• Comprehend the influence of AI on the creative industries.

This live, instructor-led course offered in Copenhagen (online or onsite) targets advanced robotics engineers and AI researchers. It focuses on utilizing Multimodal AI to fuse various sensory data streams, enabling the creation of highly autonomous and efficient robots that can see, hear, and touch.

By the conclusion of this training, participants will have the ability to:

• Integrate multimodal sensing into robotic systems.
• Design AI algorithms for effective sensor fusion and decision-making processes.
• Construct robots capable of managing complex tasks in changing environments.
• Overcome challenges associated with real-time data handling and actuation.

This instructor-led, live training in Copenhagen (available online or on-site) is tailored for intermediate-level UX/UI designers and front-end developers seeking to use Multimodal AI to create user interfaces that interpret and handle various input methods.

By the end of the session, participants will be able to:

• Design multimodal interfaces that enhance user engagement.
• Incorporate voice and visual recognition into web and mobile apps.
• Use multimodal data to develop adaptive and responsive UIs.
• Understand the ethical aspects of user data collection and processing.

This instructor-led, live training in Copenhagen (online or onsite) is tailored for intermediate-level AI researchers, data scientists, and machine learning engineers looking to build intelligent systems that process and interpret multimodal data.

By the conclusion of this training, participants will have acquired the ability to:

• Comprehend the fundamental principles of multimodal AI and its diverse applications.
• Utilize data fusion techniques to seamlessly combine disparate data sources.
• Construct and train models capable of processing visual, textual, and auditory inputs.
• Evaluate the performance metrics of multimodal AI systems.
• Address the ethical and privacy considerations inherent in multimodal data handling.