Advanced Fine-Tuning & Prompt Management in Vertex AI Training Course

This instructor-led, live training in New Zealand (online or onsite) is aimed at advanced-level machine learning professionals who wish to master cutting-edge transfer learning techniques and apply them to complex real-world problems.

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

• Understand advanced concepts and methodologies in transfer learning.
• Implement domain-specific adaptation techniques for pre-trained models.
• Apply continual learning to manage evolving tasks and datasets.
• Master multi-task fine-tuning to enhance model performance across tasks.

This instructor-led, live training in New Zealand (online or on-site) is designed for advanced-level AI maintenance engineers and MLOps professionals seeking to implement robust continual learning pipelines and effective update strategies for deployed, fine-tuned models.

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

• Design and implement continual learning workflows for deployed models.
• Mitigate catastrophic forgetting through appropriate training techniques and memory management.
• Automate monitoring and update triggers based on model drift or data changes.
• Integrate model update strategies into existing CI/CD and MLOps pipelines.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level developers, data scientists, and tech professionals who wish to leverage Google Vertex AI for creating and deploying custom AI models.

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

• Understand the capabilities and features of Google Vertex AI.
• Set up and configure the Google Vertex AI environment.
• Develop and train custom AI models using Vertex AI.
• Deploy and manage AI models on Google Cloud Platform.
• Utilise Vertex AI's tools for monitoring and optimising model performance.
• Implement best practices for AI model development and deployment.

This instructor-led, live training in New Zealand (online or on-site) is designed for advanced-level professionals who wish to deploy fine-tuned models reliably and efficiently.

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

• Understand the challenges involved in deploying fine-tuned models into production.
• Containerise and deploy models using tools such as Docker and Kubernetes.
• Implement monitoring and logging for deployed models.
• Optimise models for latency and scalability in real-world scenarios.

This instructor-led, live training in New Zealand (online or on-site) is designed for intermediate-level professionals seeking to gain practical skills in customising AI models for essential financial tasks.

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

• Understand the fundamentals of fine-tuning for finance applications.
• Leverage pre-trained models for domain-specific tasks in finance.
• Apply techniques for fraud detection, risk assessment, and financial advice generation.
• Ensure compliance with financial regulations such as GDPR and SOX.
• Implement data security and ethical AI practices in financial applications.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level to advanced-level professionals who wish to customise pre-trained models for specific tasks and datasets.

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

• Understand the principles of fine-tuning and its applications.
• Prepare datasets for fine-tuning pre-trained models.
• Fine-tune large language models (LLMs) for NLP tasks.
• Optimise model performance and address common challenges.

This instructor-led, live training in New Zealand (online or onsite) is aimed at intermediate-level developers and AI practitioners who wish to implement fine-tuning strategies for large models without the need for extensive computational resources.

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

• Understand the principles of Low-Rank Adaptation (LoRA).
• Implement LoRA for efficient fine-tuning of large models.
• Optimise fine-tuning for resource-constrained environments.
• Evaluate and deploy LoRA-tuned models for practical applications.

This instructor-led, live training in New Zealand (online or on-site) is designed for developers at beginner, intermediate, and advanced levels, as well as cloud engineers and technical product teams who want to use Google Cloud's generative AI tools to build and evaluate practical AI applications.

By the end of this training, participants will be able to: understand Google Cloud's generative AI services, create effective prompts and workflows, build simple applications using Vertex AI, and apply responsible AI practices.

This instructor-led, live training in New Zealand (available online or onsite) is tailored for developers and technical practitioners at beginner, intermediate, and advanced levels who intend to use Google Cloud to build AI agents that can automate tasks, utilise tools, and interact with business data.

By the conclusion of this training, participants will be able to: articulate AI agent concepts, construct agents using Vertex AI, connect agents to external tools and data, and deploy agents for business use cases.