Multimodal AI Training in Lyon

This instructor-led, live training in Lyon (online or onsite) is designed for AI researchers, developers, and data scientists at intermediate to advanced levels who wish to leverage DeepSeek’s multimodal capabilities for cross-modal learning, AI automation, and advanced decision-making.

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

• Implement DeepSeek’s multimodal AI for text, image, and audio applications.
• Develop AI solutions that integrate multiple data types for richer insights.
• Optimize and fine-tune DeepSeek models for cross-modal learning.
• Apply multimodal AI techniques to real-world industry use cases.

This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level to advanced-level AI developers, researchers, and multimedia engineers who wish to build AI agents capable of understanding and generating multi-modal content.

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

• Develop AI agents that process and integrate text, image, and speech data.
• Implement multi-modal models such as GPT-4 Vision and Whisper ASR.
• Optimize multi-modal AI pipelines for efficiency and accuracy.
• Deploy multi-modal AI agents in real-world applications.

This instructor-led, live training in Lyon (online or on-site) is designed for advanced AI professionals aiming to improve their prompt engineering skills for multimodal AI applications.

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

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

This instructor-led, live training in Lyon (online or onsite) is aimed at advanced-level AI developers, machine learning engineers, and researchers who wish to build custom multimodal AI models using open-source frameworks.

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

• Understand the fundamentals of multimodal learning and data fusion.
• Implement multimodal models using DeepSeek, OpenAI, Hugging Face, and PyTorch.
• Optimize and fine-tune models for text, image, and audio integration.
• Deploy multimodal AI models in real-world applications.

This instructor-led, live training in Lyon (online or onsite) is designed for intermediate to advanced industrial engineers, automation specialists, and AI developers seeking to leverage multimodal AI for quality control, predictive maintenance, and robotics in smart factories.

Upon completing this training, participants will be able to:

• Comprehend the role of multimodal AI in industrial automation.
• Integrate sensor data, image recognition, and real-time monitoring for smart factories.
• Implement predictive maintenance through AI-driven data analysis.
• Apply computer vision techniques for defect detection and quality assurance.

This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level linguists, AI researchers, software developers, and business professionals seeking to leverage multimodal AI for real-time translation and language understanding.

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

• Grasp the fundamentals of multimodal AI for language processing.
• Utilize AI models to process and translate speech, text, and images.
• Implement real-time translation using AI-powered APIs and frameworks.
• Integrate AI-driven translation into business applications.
• Analyze ethical considerations in AI-powered language processing.

This instructor-led, live training in Lyon (online or onsite) is designed for beginner to intermediate product designers, software engineers, and customer support professionals looking to enhance virtual assistants with multimodal AI.

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

• Grasp how multimodal AI improves virtual assistants.
• Integrate speech, text, and image processing into AI-powered assistants.
• Construct interactive conversational agents equipped with voice and vision capabilities.
• Utilize APIs for speech recognition, NLP, and computer vision.
• Implement AI-driven automation for customer support and user interaction.

This instructor-led live training in Lyon (online or onsite) is aimed at intermediate to advanced healthcare professionals, medical researchers, and AI developers looking to apply multimodal AI in medical diagnostics and healthcare applications.

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

• Understand the role of multimodal AI in modern healthcare.
• Integrate structured and unstructured medical data for AI-driven diagnostics.
• Apply AI techniques to analyze medical images and electronic health records.
• Develop predictive models for disease diagnosis and treatment recommendations.
• Implement speech and natural language processing (NLP) for medical transcription and patient interaction.

Vertex AI offers robust tools for constructing multimodal LLM workflows that seamlessly integrate text, audio, and image data into a unified pipeline. By leveraging long context window support and Gemini API parameters, it facilitates the development of sophisticated applications focused on planning, reasoning, and cross-modal intelligence.

This instructor-led live training (available online or onsite) is designed for intermediate to advanced practitioners aiming to design, build, and optimize multimodal AI workflows within Vertex AI.

Upon completion of this training, participants will be capable of:

• Utilizing Gemini models to handle multimodal inputs and outputs.
• Implementing long-context workflows to address complex reasoning tasks.
• Designing pipelines that effectively combine text, audio, and image analysis.
• Optimizing Gemini API parameters to enhance performance and cost efficiency.

Course Format

• Interactive lectures and discussions.
• Hands-on labs focused on multimodal workflows.
• Project-based exercises addressing real-world multimodal use cases.

Customization Options

• To request a tailored version of this course, please reach out to us to arrange details.

This instructor-led, live training in Lyon (online or onsite) is aimed at intermediate-level finance professionals, data analysts, risk managers, and AI engineers who wish to leverage multimodal AI for risk analysis and fraud detection.

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

• Understand how multimodal AI is applied in financial risk management.
• Analyze structured and unstructured financial data for fraud detection.
• Implement AI models to identify anomalies and suspicious activities.
• Leverage NLP and computer vision for financial document analysis.
• Deploy AI-driven fraud detection models in real-world financial systems.

This instructor-led live training in Lyon (online or onsite) is designed for beginner to intermediate UI/UX designers, product managers, and AI researchers who aim to elevate user experiences through multimodal AI-powered interfaces.

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

• Comprehend the fundamentals of multimodal AI and its effect on human-computer interaction.
• Create and prototype multimodal interfaces utilizing AI-driven input methods.
• Implement technologies for speech recognition, gesture control, and eye tracking.
• Evaluate the usability and efficacy of multimodal systems.

This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level content creators, digital artists, and media professionals who want to learn how to apply multimodal AI to different forms of content creation.

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

• Leverage AI tools to enhance music and video production.
• Generate unique visual art and designs using AI.
• Create interactive multimedia experiences.
• Understand the impact of AI on the creative industries.

This instructor-led, live training in Lyon (online or onsite) targets advanced robotics engineers and AI researchers who wish to utilize Multimodal AI. The goal is to integrate various sensory data streams to create more autonomous and efficient robots capable of visual, auditory, and tactile interaction.

Upon completion, participants will be able to:

• Implement multimodal sensing within robotic systems.
• Develop AI algorithms for sensor fusion and decision-making.
• Build robots capable of executing complex tasks in dynamic environments.
• Address challenges related to real-time data processing and actuation.

This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level UX/UI designers and front-end developers who aim to utilize Multimodal AI to design and implement user interfaces that can comprehend and process diverse input types.

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

• Design multimodal interfaces that enhance user engagement.
• Integrate voice and visual recognition into web and mobile applications.
• Utilize multimodal data to create adaptive and responsive UIs.
• Understand the ethical considerations of user data collection and processing.

This instructor-led, live training in Lyon (online or onsite) is designed for intermediate-level AI researchers, data scientists, and machine learning engineers who aim to create intelligent systems capable of processing and interpreting multimodal data.

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

• Grasp the fundamental principles of multimodal AI and its real-world applications.
• Apply data fusion methods to integrate various data types effectively.
• Construct and train models capable of processing visual, textual, and auditory information.
• Assess the performance of multimodal AI systems.
• Tackle ethical and privacy issues associated with multimodal data.