Prompt Engineering for Multimodal AI Training Course

Vertex AI offers sophisticated tools for fine-tuning large models and managing prompts, empowering developers and data teams to enhance model accuracy, streamline iteration workflows, and ensure rigorous evaluation through integrated libraries and services.

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

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

• Apply supervised fine-tuning techniques to Gemini models in Vertex AI.
• Implement prompt management workflows, including versioning and testing.
• Leverage evaluation libraries to benchmark and optimize AI performance.
• Deploy and monitor improved models in production environments.

Format of the Course

• Interactive lecture and discussion.
• Hands-on labs with Vertex AI fine-tuning and prompt tools.
• Case studies of enterprise model optimization.

Course Customization Options

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

This live, instructor-led training in Nigeria (online or in-person) is designed for advanced AI developers, machine learning engineers, and researchers who want to create custom multimodal AI models using open-source frameworks.

Upon completing this training, participants will be able to:

• Grasp the core principles of multimodal learning and data fusion.
• Build multimodal models using DeepSeek, OpenAI, Hugging Face, and PyTorch.
• Optimize and fine-tune models for integrating text, image, and audio inputs.
• Deploy multimodal AI models in practical, real-world scenarios.

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

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

• Understand the fundamentals of multimodal AI and its effect 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.

Vertex AI equips practitioners with robust tools to construct multimodal LLM workflows, seamlessly integrating text, audio, and image data into a unified pipeline. By leveraging long context window capabilities 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 either online or onsite, targets intermediate to advanced practitioners eager to design, build, and optimize multimodal AI workflows within Vertex AI.

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

• Utilize Gemini models for handling both multimodal inputs and outputs.
• Construct long-context workflows tailored for complex reasoning tasks.
• Design pipelines that effectively combine text, audio, and image analysis.
• Optimize Gemini API parameters to enhance performance and cost-efficiency.

Course Format

• Interactive lectures paired with discussions.
• Practical labs focused on multimodal workflows.
• Project-based exercises applied to real-world multimodal use cases.

Customization Options

• For requests regarding customized training for this course, please contact us to make arrangements.

This instructor-led, live training in Nigeria (online or onsite) is designed for intermediate to advanced AI developers, researchers, and multimedia engineers who want to create AI agents capable of understanding and generating multi-modal content.

Upon completing this training, participants will be able to:

• Create 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 enhanced efficiency and accuracy.
• Deploy multi-modal AI agents in real-world applications.

This instructor-led, live training in Nigeria (online or onsite) is aimed at intermediate-level to advanced-level AI researchers, developers, and data scientists 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 live, instructor-led training in Nigeria (online or onsite) targets intermediate to advanced 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 Nigeria (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.
• Analyze ethical considerations in AI-powered language processing.

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

Upon completing this training, participants will be able to:

• Leverage AI tools to elevate music and video production.
• Generate distinctive visual art and designs using AI.
• Develop interactive multimedia experiences.
• Gain insight into the impact of AI on the creative industries.

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

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 live, instructor-led training in Nigeria (online or onsite) is designed for beginner to intermediate-level product designers, software engineers, and customer support professionals who wish to upgrade their virtual assistants with multimodal AI.

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

• Comprehend how multimodal AI elevates the functionality of virtual assistants.
• Integrate speech, text, and image processing into AI-powered assistants.
• Develop interactive conversational agents with voice and visual capabilities.
• Leverage APIs for speech recognition, NLP, and computer vision.
• Deploy AI-driven automation to streamline customer support and user interactions.

This instructor-led, live training in Nigeria (online or onsite) is tailored for intermediate-level UX/UI designers and front-end developers who want to leverage Multimodal AI to design and implement user interfaces capable of understanding and processing various 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.
• Use multimodal data to build adaptive and responsive UIs.
• Understand the ethical considerations involved in user data collection and processing.