Continual Learning and Model Update Strategies for Fine-Tuned Models Training Course

Vertex AI equips developers and data teams with sophisticated tools for fine-tuning large language models and managing prompts. These capabilities allow teams to enhance model accuracy, streamline iterative workflows, and maintain rigorous evaluation standards through integrated libraries and services.

This instructor-led live training, available either online or onsite, is designed for intermediate to advanced practitioners aiming to boost the performance and reliability of generative AI applications. The course covers supervised fine-tuning, prompt versioning, and evaluation services within the Vertex AI environment.

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

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

Format of the Course

• Interactive lectures and discussions.
• Practical labs involving Vertex AI fine-tuning and prompt tools.
• Case studies focusing on enterprise model optimization.

Course Customization Options

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

This instructor-led, live training in Portugal (online or onsite) is designed for advanced-level machine learning professionals aiming to master cutting-edge transfer learning techniques and apply them to complex real-world challenges.

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

• Grasp 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 various tasks.

This instructor-led, live training in Portugal (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 Portugal (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 Portugal (online or on-site) is aimed at intermediate to advanced professionals who wish 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.

Delivered as an instructor-led live training in Portugal (online or onsite), this course 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.
• Optimize fine-tuning for resource-constrained environments.
• Evaluate and deploy LoRA-tuned models for practical applications.

This instructor-led, live training in Portugal (online or onsite) is aimed at advanced-level professionals who wish to master multimodal model fine-tuning for innovative AI solutions.

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

• Understand the architecture of multimodal models like CLIP and Flamingo.
• Prepare and preprocess multimodal datasets effectively.
• Fine-tune multimodal models for specific tasks.
• Optimize models for real-world applications and performance.

This instructor-led, live training in Portugal (online or onsite) is aimed at intermediate-level professionals who wish to enhance their NLP projects through the effective fine-tuning of pre-trained language models.

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

• Understand the fundamentals of fine-tuning for NLP tasks.
• Fine-tune pre-trained models such as GPT, BERT, and T5 for specific NLP applications.
• Optimize hyperparameters for improved model performance.
• Evaluate and deploy fine-tuned models in real-world scenarios.

This instructor-led, live training in Portugal (online or onsite) is aimed at advanced-level data scientists and AI engineers in the financial sector who wish to fine-tune models for applications such as credit scoring, fraud detection, and risk modeling using domain-specific financial data.

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

• Fine-tune AI models on financial datasets for improved fraud and risk prediction.
• Apply techniques such as transfer learning, LoRA, and regularization to enhance model efficiency.
• Integrate financial compliance considerations into the AI modeling workflow.
• Deploy fine-tuned models for production use in financial services platforms.

This instructor-led, live training in Portugal (online or onsite) is designed for intermediate to advanced medical AI developers and data scientists who aim to fine-tune models for clinical diagnosis, disease prediction, and forecasting patient outcomes using structured and unstructured medical data.

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

• Fine-tune AI models using healthcare datasets, including Electronic Medical Records (EMRs), imaging data, and time-series data.
• Implement transfer learning, domain adaptation, and model compression techniques within medical contexts.
• Address privacy concerns, bias mitigation, and regulatory compliance during model development.
• Deploy and monitor fine-tuned models in real-world healthcare settings.

This instructor-led live training in Portugal (online or onsite) targets advanced-level AI researchers, machine learning engineers, and developers who wish to fine-tune DeepSeek LLM models to create specialized AI applications tailored to specific industries, domains, or business needs.

Upon completion of this training, participants will be capable of:

• Comprehending the architecture and capabilities of DeepSeek models, including DeepSeek-R1 and DeepSeek-V3.
• Preparing datasets and performing data preprocessing for fine-tuning.
• Fine-tuning DeepSeek LLM for domain-specific applications.
• Efficiently optimizing and deploying fine-tuned models.

This instructor-led live training in Portugal (online or onsite) is targeted at advanced defense AI engineers and military technology developers who wish to fine-tune deep learning models for autonomous vehicles, drones, and surveillance systems, meeting stringent security and reliability standards.

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

• Fine-tune computer vision and sensor fusion models for surveillance and targeting tasks.
• Adapt autonomous AI systems to changing environments and mission profiles.
• Implement robust validation and fail-safe mechanisms in model pipelines.
• Ensure alignment with defense-specific compliance, safety, and security standards.

This instructor-led, live training in Portugal (online or onsite) is designed for intermediate-level legal tech engineers and AI developers who wish to fine-tune language models for tasks such as contract analysis, clause extraction, and automated legal research within legal service environments.

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

• Prepare and clean legal documents for fine-tuning NLP models.
• Apply fine-tuning strategies to improve model accuracy on legal tasks.
• Deploy models to assist with contract review, classification, and research.
• Ensure compliance, auditability, and traceability of AI outputs in legal contexts.

This instructor-led, live training in Portugal (online or on-site) is designed for intermediate to advanced-level machine learning engineers, AI developers, and data scientists who wish to learn how to employ QLoRA to efficiently fine-tune large models for specific tasks and customisations.

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

• Comprehend the theory behind QLoRA and quantization techniques for LLMs.
• Implement QLoRA for fine-tuning large language models in domain-specific applications.
• Optimize fine-tuning performance on limited computational resources through quantization.
• Deploy and evaluate fine-tuned models in real-world applications efficiently.

This instructor-led, live training in Portugal (online or onsite) is designed for intermediate-level embedded AI developers and edge computing specialists who want to fine-tune and optimize lightweight AI models for deployment on resource-constrained devices.

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

• Select and adapt pre-trained models suitable for edge deployment.
• Apply quantization, pruning, and other compression techniques to reduce model size and latency.
• Fine-tune models using transfer learning for task-specific performance.
• Deploy optimized models on real edge hardware platforms.