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

This instructor-led, live training in Uzbekistan (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 Uzbekistan (online or onsite) targets 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 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 Uzbekistan (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.
• Utilize Vertex AI's tools for monitoring and optimizing model performance.
• Implement best practices for AI model development and deployment.

This instructor-led, live training in Uzbekistan (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 Uzbekistan (online or onsite) targets intermediate-level professionals eager to develop practical skills in customizing AI models for critical financial tasks.

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

• Grasp the core principles of fine-tuning AI for financial applications.
• Utilize pre-trained models for specialized tasks within the finance sector.
• Apply techniques for fraud detection, risk assessment, and generating financial advice.
• Ensure adherence to financial regulations, including GDPR and SOX.
• Implement robust data security and ethical AI practices in financial software.

This instructor-led live training in Uzbekistan (online or onsite) is designed for intermediate to advanced professionals aiming to customize pre-trained models for specific tasks and datasets.

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

• Grasp the core principles of fine-tuning and its real-world applications.
• Prepare datasets effectively for fine-tuning pre-trained models.
• Fine-tune large language models (LLMs) for NLP tasks.
• Enhance model performance and resolve common challenges.

This instructor-led, live training in Uzbekistan (available online or on-site) is designed for 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 core principles of Low-Rank Adaptation (LoRA).
• Implement LoRA for efficient fine-tuning of large models.
• Optimize fine-tuning processes for environments with limited resources.
• Evaluate and deploy LoRA-tuned models in practical applications.

This instructor-led, live training in Uzbekistan (online or onsite) is designed for developers at beginner, intermediate, and advanced levels, as well as cloud engineers and technical product teams who wish to utilise 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 effective prompts and workflows, build simple applications using Vertex AI, and apply responsible AI practices.

This instructor-led, live training in Uzbekistan (available online or on-site) is designed for developers and technical professionals at beginner, intermediate, or advanced levels who intend to use Google Cloud to develop AI agents that can automate tasks, leverage tools, and interact with business data.

By the conclusion of this training, participants will be capable of: explaining AI agent concepts, constructing agents using Vertex AI, linking agents to external tools and data, and deploying agents for specific business scenarios.