Multimodal AI Training in Pierre

This instructor-led, live training (online or onsite) is aimed at intermediate to advanced-level AI researchers, developers, and data scientists who wish to leverage DeepSeek’s multimodal capabilities for cross-modal learning, AI automation, and enhanced decision-making for government. 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 more comprehensive 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 (available online or onsite) is designed for intermediate to advanced AI developers, researchers, and multimedia engineers who aim 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, enhancing capabilities for government and other sectors.

This instructor-led, live training (online or onsite) is designed for advanced-level artificial intelligence professionals who seek to enhance their prompt engineering skills for multimodal AI applications.

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

• Comprehend the foundational principles of multimodal AI and its practical applications.
• Create and refine prompts for generating text, images, audio, and video content.
• Leverage APIs for leading multimodal AI platforms such as GPT-4, Gemini, and DeepSeek-Vision.
• Develop AI-driven workflows that integrate various content formats to support efficient and effective operations for government.

This instructor-led, live training (available online or onsite) is designed for advanced-level artificial intelligence developers, machine learning engineers, and researchers who seek to build custom multimodal AI models using open-source frameworks. By the end of this training, participants will be able to: - Comprehend the core principles of multimodal learning and data fusion. - Implement multimodal models utilizing DeepSeek, OpenAI, Hugging Face, and PyTorch. - Optimize and fine-tune models for integrating text, image, and audio data. - Deploy multimodal AI models in practical applications, ensuring alignment with public sector workflows and governance standards for government.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced industrial engineers, automation specialists, and artificial intelligence developers who aim to apply multimodal AI for enhancing quality control, predictive maintenance, and robotics in smart factories. By the end of 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 systems for efficient factory operations. - Implement predictive maintenance strategies using AI-driven data analysis. - Utilize computer vision techniques for defect detection and quality assurance, ensuring robust performance and reliability for government applications.

This instructor-led, live training (online or onsite) is designed for intermediate-level linguists, artificial intelligence researchers, software developers, and business professionals who aim to leverage multimodal AI for real-time translation and language understanding. By the end of this training, participants will be able to: - Comprehend the foundational principles of multimodal AI in 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 for government and private sector use. - Evaluate ethical considerations in AI-powered language processing.

This instructor-led, live training in [location] (online or onsite) is aimed at beginner to intermediate-level product designers, software engineers, and customer support professionals who wish to enhance virtual assistants with multimodal AI. By the end of this training, participants will be able to: - Understand how multimodal AI improves the functionality of virtual assistants. - Integrate speech, text, and image processing in AI-powered assistants. - Develop interactive conversational agents with voice and vision capabilities. - Utilize APIs for speech recognition, natural language processing (NLP), and computer vision. - Implement AI-driven automation for customer support and user interaction, enhancing efficiency and service quality for government operations.

This instructor-led, live training in [location] (online or onsite) is designed for intermediate to advanced healthcare professionals, medical researchers, and AI developers who seek to apply multimodal AI in medical diagnostics and healthcare applications for government. By the end of this training, participants will be able to: - Comprehend the role of multimodal AI in modern healthcare. - Integrate structured and unstructured medical data to enhance AI-driven diagnostics. - Utilize AI techniques to analyze medical images and electronic health records. - Construct predictive models for disease diagnosis and treatment recommendations. - Implement speech and natural language processing (NLP) technologies for medical transcription and patient interaction.

Vertex AI provides robust tools for developing multimodal large language model (LLM) workflows that seamlessly integrate text, audio, and image data into a single pipeline. With support for long context windows and Gemini API parameters, it facilitates advanced applications in planning, reasoning, and cross-modal intelligence. This instructor-led, live training (online or onsite) is designed for intermediate to advanced-level practitioners who aim to design, build, and optimize multimodal AI workflows using Vertex AI. By the end of this training, participants will be able to: - Utilize Gemini models for handling multimodal inputs and outputs. - Implement long-context workflows for complex reasoning tasks. - Design pipelines that incorporate text, audio, and image analysis. - Optimize Gemini API parameters to enhance performance and cost efficiency. **Format of the Course** - Interactive lecture and discussion - Hands-on labs with multimodal workflows - Project-based exercises for applied multimodal use cases **Course Customization Options** - To request a customized training for government or other specific needs, please contact us to arrange.

This instructor-led, live training (available online or onsite) is designed for intermediate-level finance professionals, data analysts, risk managers, and artificial intelligence engineers who wish to utilize multimodal AI for enhancing risk analysis and fraud detection. By the end of this training, participants will be able to: - Comprehend how multimodal AI is applied in financial risk management. - Analyze both structured and unstructured financial data for identifying potential fraud. - Implement AI models to detect anomalies and suspicious activities. - Utilize natural language processing (NLP) and computer vision techniques for the analysis of financial documents. - Deploy AI-driven fraud detection systems in real-world financial environments, ensuring alignment with regulatory requirements for government.

This instructor-led, live training (available online or onsite) is designed for government UI/UX designers, product managers, and AI researchers at beginner to intermediate levels who aim to enhance user experiences through multimodal AI-powered interfaces. By the end of this training, participants will be able to: - Understand the fundamentals of multimodal AI and its impact on human-computer interaction. - Design and prototype multimodal interfaces using AI-driven input methods. - Implement speech recognition, gesture control, and eye-tracking technologies. - Evaluate the effectiveness and usability of multimodal systems.

This instructor-led, live training in [location] (online or onsite) is designed for intermediate-level content creators, digital artists, and media professionals who wish to explore how multimodal artificial intelligence can be utilized in various forms of content creation for government and other sectors. 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 using AI. - Develop interactive multimedia experiences. - Comprehend the impact of AI on the creative industries.

This instructor-led, live training (available online or on-site) is designed for advanced-level robotics engineers and AI researchers who aim to utilize Multimodal AI for government applications. The goal is to integrate various sensory data to create more autonomous and efficient robots capable of seeing, hearing, and touching. By the end of this training, participants will be able to: - Implement multimodal sensing in robotic systems. - Develop AI algorithms for sensor fusion and decision-making. - Create robots that can perform complex tasks in dynamic environments. - Address challenges in real-time data processing and actuation.

This instructor-led, live training (available online or on-site) is designed for intermediate-level UX/UI designers and front-end developers who seek to leverage Multimodal AI to create and implement user interfaces that can interpret and process diverse forms of input.

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 for government.
• Utilize multimodal data to develop adaptive and responsive UIs.
• Understand the ethical considerations of user data collection and processing in public sector contexts.

This instructor-led, live training in [location] (online or onsite) is aimed at intermediate-level AI researchers, data scientists, and machine learning engineers who wish to develop intelligent systems capable of processing and interpreting multimodal data for government applications. By the end of this training, participants will be able to: - Understand the principles of multimodal AI and its various applications. - Implement data fusion techniques to integrate different types of data. - Build and train models that can process visual, textual, and auditory information effectively. - Evaluate the performance of multimodal AI systems. - Address ethical and privacy concerns related to the use of multimodal data for government.