Multimodal AI Training in Gaia

This instructor-led, live training in Gaia (online or on-site) is designed for intermediate to advanced-level AI researchers, developers, and data scientists seeking to harness DeepSeek’s multimodal features for cross-modal learning, AI automation, and enhanced decision-making.

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

• Implement DeepSeek’s multimodal AI for applications involving text, images, and audio.
• Create AI solutions that integrate diverse data types to yield richer insights.
• Optimize and fine-tune DeepSeek models for effective cross-modal learning.
• Apply multimodal AI techniques to practical industry use cases.

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

Upon completing this training, participants will be able to:

• Grasp the fundamentals of multimodal AI and its practical applications.
• Design and optimise prompts for generating text, images, audio, and video.
• Leverage APIs for multimodal AI platforms such as GPT-4, Gemini, and DeepSeek-Vision.
• Create AI-driven workflows that integrate multiple content formats.

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

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

• Grasping the core principles of multimodal learning and data fusion.
• Constructing multimodal models leveraging DeepSeek, OpenAI, Hugging Face, and PyTorch.
• Optimizing and fine-tuning models for the seamless integration of text, image, and audio.
• Deploying multimodal AI models within real-world contexts.

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

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

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

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

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

• Comprehend the core principles of multimodal AI for language processing.
• Utilize AI models to process and translate speech, text, and images.
• Deploy real-time translation solutions using AI-driven APIs and frameworks.
• Integrate AI-powered translation into business applications.
• Evaluate ethical implications associated with AI-enabled language processing.

This instructor-led, live training in Gaia (online or onsite) is aimed at beginner to intermediate product designers, software engineers, and customer support professionals who wish 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.
• Develop interactive conversational agents with voice and vision capabilities.
• Use APIs for speech recognition, NLP, and computer vision.
• Implement AI-driven automation for customer support and user interaction.

This instructor-led, live training in Gaia (online or onsite) is aimed at intermediate-level to advanced-level healthcare professionals, medical researchers, and AI developers who wish 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.

This live training in Gaia empowers practitioners to design, construct, and optimise multimodal LLM workflows within Vertex AI. The curriculum explores Gemini models, long-context reasoning, and pipelines that merge text, audio, and image data. Through hands-on labs, the course ensures practical competence for real-world application.

This instructor-led, live training in Gaia (online or on-site) is designed for intermediate-level finance professionals, data analysts, risk managers, and AI engineers who wish to harness multimodal AI for risk analysis and fraud detection.

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

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

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

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

• Grasping the core principles of multimodal AI and its influence on human-computer interaction.
• Designing and prototyping multimodal interfaces utilizing AI-driven input methods.
• Deploying technologies for speech recognition, gesture control, and eye-tracking.
• Assessing the usability and effectiveness of multimodal systems.

This instructor-led, live training in Gaia (online or onsite) is designed for intermediate-level content creators, digital artists, and media professionals seeking to learn how multimodal AI can be applied to various forms of content creation.

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

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

This instructor-led, live training in Gaia (online or onsite) is designed for advanced robotics engineers and AI researchers who wish to utilize Multimodal AI for integrating various sensory data to create more autonomous and efficient robots that can see, hear, and touch.

Upon completion of this training, 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.
• Tackle challenges related to real-time data processing and actuation.

This instructor-led, live training in Gaia (online or onsite) is aimed at intermediate-level UX/UI designers and front-end developers who wish to utilize Multimodal AI to design and implement user interfaces that can understand and process various forms of input.

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

• Design multimodal interfaces that improve 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 Gaia (available online or onsite) is designed for intermediate-level AI researchers, data scientists, and machine learning engineers aiming to develop intelligent systems capable of processing and interpreting multimodal data.

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

• Grasp the core principles of multimodal AI and its practical applications.
• Apply data fusion techniques to integrate various data types.
• Construct and train models capable of processing visual, textual, and auditory information.
• Assess the performance of multimodal AI systems.
• Address ethical and privacy issues associated with multimodal data.