Multimodal AI for Content Creation Training Course

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

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

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

This live, instructor-led session in Latvia (online or on-site) is tailored for UI/UX designers, product managers, and AI researchers with beginner to intermediate experience who aim to refine user experiences using multimodal AI interfaces.

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

• Comprehend the basics of multimodal AI and its effect on human-computer interaction.
• Design and prototype multimodal interfaces leveraging AI-driven inputs.
• Integrate speech recognition, gesture control, and eye-tracking capabilities.
• Analyze the efficacy and usability of multimodal systems.

This live training in Latvia guides practitioners through the design, construction, and optimization of multimodal LLM workflows in Vertex AI. The curriculum explores Gemini models, long-context reasoning, and pipelines that integrate text, audio, and image data. With a focus on hands-on labs, it ensures participants are prepared for practical, real-world implementation.

This instructor-led live training in Latvia (delivered online or onsite) is tailored for intermediate to advanced AI developers, researchers, and multimedia engineers seeking to build AI agents proficient in understanding and generating multi-modal content.

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

• Design AI agents that handle and merge text, image, and speech data.
• Apply multi-modal models, such as GPT-4 Vision and Whisper ASR.
• Optimize multi-modal AI workflows for superior efficiency and accuracy.
• Implement multi-modal AI agents in live operational environments.

This live, instructor-led training in Latvia (delivered online or on-site) targets AI researchers, developers, and data scientists at intermediate to advanced levels seeking to exploit DeepSeek’s multimodal capabilities for cross-modal learning, AI automation, and sophisticated decision-making.

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

• Execute DeepSeek’s multimodal AI for text, image, and audio-centric tasks.
• Construct AI solutions that merge multiple data types for enriched analytical insights.
• Optimize and fine-tune DeepSeek models to enhance cross-modal learning performance.
• Utilize multimodal AI techniques to address practical industry challenges.

This instructor-led, live training in Latvia (online or onsite) is aimed at intermediate-level to advanced-level industrial engineers, automation specialists, and AI developers who wish to apply multimodal AI for quality control, predictive maintenance, and robotics in smart factories.

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

• Understand 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 Latvia (online or on-site) is designed for intermediate-level linguists, AI researchers, software engineers, and business professionals aiming to utilize multimodal AI for real-time translation and language comprehension.

Upon completion, participants will be equipped to:

• Grasp the core principles of multimodal AI in language processing.
• Utilize AI models to interpret and translate audio, text, and imagery.
• Deploy real-time translation via AI-driven APIs and frameworks.
• Embed AI-based translation into enterprise applications.
• Evaluate ethical factors in AI-enabled language processing.

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

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

• Understand the core principles of multimodal AI and its real-world applications.
• Apply data fusion techniques to integrate diverse data types.
• Construct and train models capable of processing visual, textual, and auditory information.
• Evaluate the performance metrics of multimodal AI systems.
• Address ethical and privacy issues concerning multimodal data.

This instructor-led, live training conducted in Latvia (available online or onsite) targets intermediate-level finance professionals, data analysts, risk managers, and AI engineers seeking to utilize multimodal AI for risk analysis and fraud detection.

Following this training, participants will be capable of:

• Comprehending the use of multimodal AI in financial risk management.
• Examining structured and unstructured financial data for fraud identification.
• Deploying AI models to detect anomalies and suspicious actions.
• Applying NLP and computer vision for the analysis of financial documents.
• Integrating AI-driven fraud detection models into operational financial systems.

This live, instructor-led training in Latvia (online or onsite) is designed for intermediate to advanced healthcare professionals, medical researchers, and AI developers seeking to implement multimodal AI in medical diagnostics and healthcare applications.

By the conclusion of this program, participants will be capable of:

• Grasping the role of multimodal AI in modern healthcare systems.
• Merging structured and unstructured medical data for AI-powered diagnostics.
• Applying AI techniques to interpret medical images and electronic health records.
• Building predictive models for disease diagnosis and treatment guidance.
• Employing speech and natural language processing (NLP) for medical transcription and patient communication.

This live, instructor-led training, offered in Latvia via online or on-site sessions, targets advanced robotics engineers and AI researchers aiming to apply Multimodal AI for the integration of varied sensory inputs. The objective is to enable the creation of more autonomous and efficient robotic systems that possess the capabilities to see, hear, and touch.

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

• Integrate multimodal sensing into robotic systems.
• Formulate AI algorithms for effective sensor fusion and decision-making.
• Develop robots that can manage complex tasks in fluid, dynamic environments.
• Overcome obstacles related to real-time data handling and actuation.

This instructor-led live training, delivered in Latvia (either online or onsite), is tailored for product designers, software engineers, and customer support professionals with beginner to intermediate experience who aim to augment virtual assistants with multimodal AI.

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

• Comprehend the mechanisms by which multimodal AI enhances virtual assistants.
• Integrate speech, text, and image processing into AI-driven assistants.
• Develop interactive conversational agents with robust voice and vision capabilities.
• Leverage APIs for speech recognition, NLP, and computer vision.
• Apply AI-driven automation to improve customer support and user engagement.

This instructor-led live training, offered in Latvia (online or onsite), targets intermediate UX/UI designers and front-end developers. The program equips professionals with the skills to apply Multimodal AI in designing and building user interfaces that effectively understand and process diverse inputs.

By the end of the course, participants will be capable of:

• Creating multimodal interfaces that enhance user engagement.
• Integrating voice and visual recognition into web and mobile platforms.
• Leveraging multimodal data to develop adaptive and responsive UIs.
• Understanding the ethical frameworks surrounding user data collection and processing.

This live, instructor-led training, available in Latvia (either online or onsite), is tailored for advanced AI professionals seeking to elevate their prompt engineering expertise in the realm of multimodal AI.

By the conclusion of the course, participants will be able to:

• Comprehend the basic mechanics of multimodal AI and its industry applications.
• Engineer and refine prompts for the generation of text, images, audio, and video.
• Apply APIs from multimodal platforms such as GPT-4, Gemini, and DeepSeek-Vision.
• Build AI-driven workflows that merge multiple content types.