Fine-Tuning Training in Bangkok

Targeting advanced defense AI engineers and military technology developers, this live, instructor-led training in Bangkok (online or onsite) focuses on fine-tuning deep learning models for autonomous vehicles, drones, and surveillance systems. The program ensures that all adaptations meet stringent security and reliability standards.

By the end of the program, participants will be capable of:

• Optimizing computer vision and sensor fusion models for enhanced surveillance and targeting.
• Adjusting autonomous AI systems to accommodate varying environments and mission requirements.
• Establishing robust validation and fail-safe mechanisms within model pipelines.
• Aligning solutions with defense-specific compliance, safety, and security benchmarks.

This live, instructor-led training held in Bangkok (delivered online or onsite) caters to intermediate-level legal tech engineers and AI developers aiming to fine-tune language models for essential tasks including contract analysis, clause extraction, and automated legal research in service-oriented legal environments.

By the conclusion of this session, participants will be capable of:

• Preparing and cleaning legal documents specifically for NLP fine-tuning processes.
• Employing fine-tuning strategies to boost model accuracy for legal-specific tasks.
• Deploying models to facilitate contract review, document classification, and research activities.
• Guaranteeing compliance, auditability, and traceability of AI outputs within legal contexts.

Tailored for intermediate to advanced medical AI developers and data scientists, this instructor-led live training Bangkok (online or onsite) offers specialized skills in fine-tuning models for clinical diagnosis, disease prediction, and patient outcome forecasting, leveraging both structured and unstructured medical data.

By the conclusion of this training, participants will be capable of:

• Fine-tuning AI models using healthcare datasets, including EMRs, imaging, and time-series data.
• Implementing transfer learning, domain adaptation, and model compression for medical applications.
• Managing privacy, bias, and regulatory compliance in model development.
• Deploying and monitoring fine-tuned models in practical healthcare settings.

This instructor-led, live training in Bangkok (offered online or on-site) is curated for senior data scientists and AI engineers in the financial domain looking to optimize models for key functions like credit assessment, fraud prevention, and risk analysis by utilizing specialized financial data.

By the conclusion of this course, participants will be capable of:

• Enhancing AI models with financial datasets to improve the precision of fraud and risk forecasts.
• Implementing methods such as transfer learning, LoRA, and regularization to drive better model performance and efficiency.
• Incorporating regulatory and compliance standards into the AI modeling process.
• Deploying optimized models for real-world application in financial service platforms.

This live, instructor-led training in Bangkok (offered online or on-site) targets advanced AI maintenance engineers and MLOps professionals seeking to deploy robust continuous learning pipelines and effective updating strategies for their fine-tuned, production models.

Following this training, participants will be capable of:

• Designing and executing continuous learning workflows for models in production.
• Mitigating catastrophic forgetting through effective training and memory management.
• Automating monitoring and update triggers based on model drift or data evolution.
• Embedding model update strategies within existing CI/CD and MLOps pipelines.

This instructor-led, live training in Bangkok (available online or onsite) targets intermediate embedded AI developers and edge computing specialists. It is tailored for those looking to fine-tune and optimize lightweight AI models for deployment on resource-constrained devices.

By the end of the program, participants will be able to:

• Choose and adapt pre-trained models that suit edge deployment requirements.
• Implement quantization, pruning, and additional compression techniques to lower model size and latency.
• Apply transfer learning to fine-tune models for improved task-specific outcomes.
• Deploy optimized models onto actual edge hardware platforms.

This instructor-led, live course in Bangkok (online or onsite) is designed for advanced computer vision engineers and AI developers aiming to fine-tune VLMs like CLIP and Flamingo to enhance performance on industry-specific visual-text tasks.

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

• Grasp the architecture and pretraining approaches of vision-language models.
• Refine VLMs for tasks including classification, retrieval, captioning, and multimodal QA.
• Manage datasets and utilize PEFT methods to lower resource demands.
• Assess and roll out customized VLMs in live production environments.

This live, instructor-led training in Bangkok (available online or onsite) targets intermediate-level ML engineers and AI compliance professionals aiming to identify, assess, and reduce safety risks and biases in fine-tuned language models.

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

• Understand the ethical and regulatory context for safe AI systems.
• Identify and evaluate common forms of bias in fine-tuned models.
• Apply bias mitigation techniques during and after training.
• Design and audit models for safety, transparency, and fairness.

This live, instructor-led course offered in Bangkok (online or onsite) is designed for intermediate NLP engineers and knowledge management teams seeking to refine RAG pipelines. The goal is to boost performance across question answering, enterprise search, and summarization tasks.

Participants will leave the session capable of:

• Comprehending the structural and functional mechanics of RAG systems.
• Customizing retriever and generator modules for specific domain datasets.
• Measuring RAG effectiveness and applying enhancements via PEFT techniques.
• Rolling out optimized RAG systems for internal or live production use.

This instructor-led live training, conducted in Bangkok (either online or onsite), is tailored for intermediate-level ML practitioners and AI developers who aim to customize and deploy open-weight models such as LLaMA, Mistral, and Qwen for targeted business or internal operations.

Upon completing this training, participants will be capable of:

• Understanding the landscape and key differences among open-source LLMs.
• Preparing datasets and configuring fine-tuning settings for models like LLaMA, Mistral, and Qwen.
• Running fine-tuning pipelines with Hugging Face Transformers and PEFT.
• Evaluating, saving, and deploying refined models in secure environments.

This live, instructor-led training, offered in Bangkok (either online or on-site), is designed for intermediate data scientists and AI engineers who aim to fine-tune large language models with enhanced affordability and efficiency. The curriculum focuses on techniques such as LoRA, Adapter Tuning, and Prefix Tuning.

By the end of the program, participants will have the ability to:

• Comprehend the theory driving parameter-efficient fine-tuning approaches.
• Implement LoRA, Adapter Tuning, and Prefix Tuning utilizing Hugging Face PEFT.
• Evaluate the performance and cost implications of PEFT methods against full fine-tuning.
• Deploy and scale fine-tuned LLMs with lower demands on compute and storage resources.

This live, instructor-led training in Bangkok (available online or on-site) targets intermediate to advanced machine learning engineers, AI developers, and data scientists seeking to efficiently fine-tune large models for specific tasks and customizations using QLoRA.

By the end of the session, participants will be equipped to:

• Comprehend the theory behind QLoRA and quantization methods for LLMs.
• Implement QLoRA for fine-tuning large language models in domain-specific contexts.
• Optimize fine-tuning performance on constrained hardware using quantization.
• Deploy and evaluate fine-tuned models effectively in real-world applications.

This live, instructor-led program, delivered in Bangkok (either online or on-site), targets advanced machine learning engineers and AI researchers looking to utilize RLHF for fine-tuning large AI models to achieve superior performance, safety, and alignment.

By the conclusion of the course, attendees will be able to:

• Comprehend the fundamental theories behind RLHF and its importance in modern AI advancements.
• Create and deploy reward models based on human input to direct reinforcement learning workflows.
• Apply RLHF strategies to fine-tune large language models, ensuring their outputs reflect human preferences.
• Implement best practices for scaling RLHF processes to meet the demands of production-grade AI systems.

This live, instructor-led training in Bangkok (available online or on-site) is designed for intermediate-level professionals aiming to build practical skills in adapting AI models for essential financial functions.

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

• Comprehend the basics of model refinement for financial applications.
• Apply pre-trained models to solve specific financial challenges.
• Use techniques for fraud identification, risk evaluation, and generating financial advice.
• Ensure adherence to financial regulations such as GDPR and SOX.
• Embed data security and ethical AI practices into financial systems.

This live, instructor-led training is conducted in Bangkok (either online or onsite) and is specifically designed for advanced professionals looking to sharpen their skills in identifying and solving fine-tuning challenges for machine learning models.

By the conclusion of this training, participants will be capable of:

• Diagnosing issues such as overfitting, underfitting, and data imbalance.
• Applying strategies to improve model convergence.
• Optimizing fine-tuning pipelines for enhanced performance.
• Troubleshooting training processes using practical tools and techniques.

This live, instructor-led training in Bangkok (online or onsite) is tailored for advanced professionals seeking to master the techniques required for optimizing large models to achieve cost-effective fine-tuning in practical applications.

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

• Recognize the specific obstacles involved in fine-tuning large models.
• Execute distributed training approaches for large model architectures.
• Employ model quantization and pruning to enhance efficiency.
• Optimize hardware usage for fine-tuning processes.
• Deploy fine-tuned models successfully into production environments.

This instructor-led, live training in Bangkok (online or onsite) is tailored for intermediate-level professionals seeking to leverage prompt engineering and few-shot learning to optimize LLM performance for real-world applications.

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

• Comprehend the core principles of prompt engineering and few-shot learning.
• Design effective prompts for a range of NLP tasks.
• Utilize few-shot techniques to adapt LLMs with limited data.
• Optimize LLM performance for practical use cases.

This live, instructor-led training, accessible via online or on-site sessions, is designed for advanced professionals aiming to excel in multimodal model fine-tuning for groundbreaking AI applications.

By the conclusion of this training, participants will possess the ability to:

• Grasp the architectural fundamentals of multimodal models like CLIP and Flamingo.
• Effectively prepare and preprocess multimodal datasets.
• Execute fine-tuning processes for multimodal models aligned with specific tasks.
• Enhance model performance and readiness for real-world implementations.

This live, instructor-led program in Bangkok (delivered online or on-site) is tailored for advanced AI researchers, machine learning engineers, and developers aiming to fine-tune DeepSeek LLMs to build specialized AI applications aligned with specific industry, domain, or business objectives.

By the conclusion of this program, participants will be capable of:

• Comprehending the architecture and potential of DeepSeek models, including DeepSeek-R1 and DeepSeek-V3.
• Preparing and preprocessing data for effective fine-tuning.
• Applying fine-tuning techniques to DeepSeek LLMs for domain-specific use cases.
• Optimizing and deploying fine-tuned models with efficiency.

Available in Bangkok, this live, instructor-led session (either online or onsite) is tailored for advanced professionals seeking to deploy fine-tuned models with high reliability and efficiency.

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

• Identify and address the complexities of deploying fine-tuned models in production.
• Containerize and release models utilizing Docker and Kubernetes.
• Set up comprehensive monitoring and logging for active model deployments.
• Enhance model performance for latency and scalability in real-world contexts.

This live, instructor-led program in Bangkok (delivered online or onsite) is designed for advanced machine learning professionals seeking to excel in cutting-edge transfer learning and apply these skills to complex industry problems.

By the conclusion of this session, attendees will be able to:

• Grasp the sophisticated concepts and techniques underpinning transfer learning.
• Deploy domain-specific adaptation methods for pre-trained architectures.
• Leverage continual learning to address evolving task requirements and data streams.
• Enhance cross-task model performance through advanced multi-task fine-tuning.

This instructor-led, live training in Bangkok (online or onsite) is tailored for beginner to intermediate machine learning professionals aiming to optimize the efficiency and performance of AI projects through the application of transfer learning techniques.

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

• Grasp the fundamental principles and advantages of transfer learning.
• Examine widely used pre-trained models and their relevant applications.
• Execute fine-tuning of pre-trained models for bespoke tasks.
• Utilize transfer learning to address practical challenges in NLP and computer vision.

This instructor-led live training, conducted in Bangkok (either online or on-site), targets intermediate-level developers and AI professionals seeking to implement fine-tuning strategies for large models without necessitating heavy computational resources.

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

• Grasp the fundamental principles of Low-Rank Adaptation (LoRA).
• Utilize LoRA for the efficient fine-tuning of large-scale models.
• Optimize fine-tuning workflows for environments with limited resources.
• Evaluate and implement LoRA-adjusted models in practical scenarios.

This instructor-led, live training in Bangkok (online or onsite) is tailored for intermediate to advanced professionals looking to customize pre-trained models for specific tasks and datasets.

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

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

This live, instructor-led training in Bangkok (virtual or on-site) is designed for mid-level professionals aiming to optimize their NLP projects by effectively adapting pre-trained language models.

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

• Comprehend the core concepts of model adaptation for NLP tasks.
• Refine pre-trained architectures such as GPT, BERT, and T5 for specific NLP use cases.
• Adjust hyperparameters to boost model performance.
• Validate and launch refined models in production environments.