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

This instructor-led, live training in Mexico (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 Mexico (online or onsite) is designed for advanced-level AI maintenance engineers and MLOps professionals who want 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 proper training 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 Mexico (online or onsite) is designed for intermediate-level developers, data scientists, and technology professionals who want to leverage Google Vertex AI to create and deploy custom AI models.

Upon completing 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.
• Use Vertex AI's tools to monitor and optimize model performance.
• Apply best practices for AI model development and deployment.

This instructor-led, live training in Mexico (online or onsite) is aimed at 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 of deploying fine-tuned models into production.
• Containerize and deploy models using tools like Docker and Kubernetes.
• Implement monitoring and logging for deployed models.
• Optimize models for latency and scalability in real-world scenarios.

This instructor-led, live training in Mexico (online or onsite) is aimed at intermediate-level professionals who wish to gain practical skills in customizing AI models for critical 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 Mexico (online or onsite) is designed for intermediate to advanced-level professionals who want to customize 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.
• Optimize model performance and address common challenges.

This instructor-led, live training in Mexico (online or in-person) is designed for intermediate developers and AI practitioners who aim to implement fine-tuning strategies for large models without relying on heavy computational resources.

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

• Understand the fundamental principles of Low-Rank Adaptation (LoRA).
• Implement LoRA for efficient fine-tuning of large models.
• Optimize fine-tuning workflows for environments with limited resources.
• Evaluate and deploy LoRA-tuned models for practical applications.

This instructor-led, live training in Mexico (online or onsite) is aimed at beginner-level / intermediate-level / advanced-level developers, cloud engineers, and technical product teams who wish to use Google Cloud generative AI tools to build and evaluate practical AI applications.

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

This live, instructor-led training in Mexico, offered either online or on-site, is designed for developers and technical practitioners of all levels (beginner to advanced) who intend to leverage Google Cloud to create AI agents that can automate tasks, utilize tools, and interact with business data.

By the conclusion of this program, participants will be equipped to explain AI agent concepts, construct agents using Vertex AI, link agents to external tools and datasets, and deploy these agents for real-world business scenarios.