Prompt Engineering for Multimodal AI Training Course

Vertex AI delivers advanced tools for fine-tuning large-scale models and managing prompts, empowering development and data teams to enhance model accuracy, streamline iteration workflows, and uphold rigorous evaluation standards using built-in libraries and services.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced practitioners seeking to improve the performance and reliability of generative AI applications through supervised fine-tuning, prompt versioning, and evaluation capabilities within Vertex AI.

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

• Apply supervised fine-tuning techniques to Gemini models within Vertex AI.
• Implement prompt management workflows, including version control and testing.
• Leverage evaluation libraries to benchmark and optimise AI performance.
• Deploy and monitor enhanced models in production environments.

Course Format

• Interactive lectures and group discussions.
• Practical labs featuring Vertex AI fine-tuning and prompt management tools.
• Real-world case studies showcasing enterprise model optimisation.

Course Customisation Options

• To request a customised training session for this course, please contact us to arrange.

This instructor-led, live training in New Zealand (available online or on-site) is designed for advanced-level AI developers, machine learning engineers, and researchers who aim to build custom multimodal AI models using open-source frameworks.

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

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

This instructor-led, live training in New Zealand (online or on-site) is designed for beginner to intermediate-level UI/UX designers, product managers, and AI researchers seeking to enrich user experiences via multimodal, AI-powered interfaces.

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

• Grasp the fundamentals of multimodal AI and its influence on human-computer interaction.
• Design and prototype multimodal interfaces leveraging AI-driven input techniques.
• Implement speech recognition, gesture control, and eye-tracking technologies.
• Assess the effectiveness and usability of multimodal systems.

Vertex AI offers robust tools for developing multimodal LLM workflows that seamlessly integrate text, audio, and image data into a unified pipeline. With support for extended context windows and configurable Gemini API parameters, it enables sophisticated applications in planning, reasoning, and cross-modal intelligence.

This instructor-led, live training (available online or on-site) is designed for intermediate to advanced-level practitioners who aim to design, build, and optimise multimodal AI workflows within Vertex AI.

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

• Leverage Gemini models for multimodal inputs and outputs.
• Implement long-context workflows to support complex reasoning tasks.
• Design pipelines that integrate analysis of text, audio, and images.
• Optimise Gemini API parameters for both performance and cost efficiency.

Course Format

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

Course Customisation Options

• To request a customised version of this course, please contact us to arrange.

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate to advanced-level AI developers, researchers, and multimedia engineers who aspire to build AI agents capable of understanding and generating multi-modal content.

By the conclusion 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.
• Optimise multi-modal AI pipelines for efficiency and accuracy.
• Deploy multi-modal AI agents in real-world applications.

This instructor-led, live training in New Zealand (online or on-site) is designed for 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.

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 to generate richer insights.
• Optimise 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 New Zealand (delivered online or on-site) is designed for intermediate to advanced-level industrial engineers, automation specialists, and AI developers who wish to apply multimodal AI to quality control, predictive maintenance, and robotics within smart factories.

By the conclusion 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 factory environments.
• Implement predictive maintenance strategies using AI-driven data analysis.
• Apply computer vision techniques for defect detection and quality assurance.

This instructor-led, live training in New Zealand (online or on-site) is aimed at 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:

• Understand the fundamentals of multimodal AI for language processing.
• Use 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.
• Analyse ethical considerations in AI-powered language processing.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level AI researchers, data scientists, and machine learning engineers who wish to create intelligent systems that can process and interpret multimodal data.

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

• Understand the principles of multimodal AI and its applications.
• Implement data fusion techniques to combine different types of data.
• Build and train models that can process visual, textual, and auditory information.
• Evaluate the performance of multimodal AI systems.
• Address ethical and privacy concerns related to multimodal data.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level content creators, digital artists, and media professionals who wish 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:

• Use 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 New Zealand (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.

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

• Understand how multimodal AI is applied in financial risk management.
• Analyse 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 New Zealand (online or on-site) is designed for intermediate 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 analyse 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 instructor-led, live training in New Zealand (available online or onsite) is designed for advanced-level robotics engineers and AI researchers who wish to leverage Multimodal AI to integrate diverse sensory data, creating more autonomous and efficient robots that can see, hear, and touch.

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

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

This instructor-led, live training in New Zealand (available online or on-site) is designed for beginner to intermediate-level product designers, software engineers, and customer support professionals seeking to enrich virtual assistants with multimodal AI.

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

• Understand how multimodal AI enhances virtual assistants.
• Integrate speech, text, and image processing into AI-powered assistants.
• Build interactive conversational agents with voice and vision capabilities.
• Utilise APIs for speech recognition, natural language processing (NLP), and computer vision.
• Implement AI-driven automation for customer support and user interaction.

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level UX/UI designers and front-end developers who wish to leverage Multimodal AI to design and implement user interfaces capable of understanding and processing 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.
• Use multimodal data to create adaptive and responsive user interfaces.
• Understand the ethical implications of collecting and processing user data.