Erbil Rotana

Gulan Street, Erbil - Kurdistan, Iraq, 44001

State of the art 7 fully equipped meeting & events venues with flexible seating plans to accommodate all requests. The Grand Ballroom with a capacity of 1000 persons can be divided into 2 sections and is a perfect venue for local and international seminars, weddings, conferences or any event. Erbil Rotana offers the latest technological Audio visual equipments to serve and exceed your expectations. Treasured time, our promise to you with our exceptional wedding packages tailor-made with idyllic settings. Our team is ready to offer you expert assistance – allowing you to look forward to your special day with ease and assurance. You will always find us at your convenience. Erbil Rotana is strategically located ten minutes away from Erbil International Airport, the main International fair ground and business centres. The hotel is adjacent to the English and Italian villages and opposite the beautiful park Sami Abdul Rahman; the largest park in Iraq. The hotel’s location gives its guests an opportunity to explore touristic sites like the historical “Citadel” and down town bazaars which makes the property convenient for the business and leisure travelers with its luxurious accommodation, wide variety of restaurants and meeting facilities.

Explore Our Courses

Fine-Tuning Defense AI for Autonomous Systems and Surveillance

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at advanced-level defense AI engineers and military technology developers who wish to fine-tune deep learning models for use in autonomous vehicles, drones, and surveillance systems while 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.
Read more...

Fine-Tuning Legal AI Models: Contract Review and Legal Research

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at intermediate-level legal tech engineers and AI developers who wish to fine-tune language models for tasks like contract analysis, clause extraction, and automated legal research in 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.
Read more...

Fine-Tuning AI for Healthcare: Medical Diagnosis and Predictive Analytics

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at intermediate-level to advanced-level medical AI developers and data scientists who wish to fine-tune models for clinical diagnosis, disease prediction, and patient outcome forecasting using structured and unstructured medical data.By the end of this training, participants will be able to:
  • Fine-tune AI models on healthcare datasets including EMRs, imaging, and time-series data.
  • Apply transfer learning, domain adaptation, and model compression in medical contexts.
  • Address privacy, bias, and regulatory compliance in model development.
  • Deploy and monitor fine-tuned models in real-world healthcare environments.
Read more...

Fine-Tuning AI for Financial Services: Risk Prediction and Fraud Detection

 14 Hours
This instructor-led, live training in Erbil (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.
Read more...

Continual Learning and Model Update Strategies for Fine-Tuned Models

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at advanced-level AI maintenance engineers and MLOps professionals who wish 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.
Read more...

Fine-Tuning Lightweight Models for Edge AI Deployment

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at intermediate-level embedded AI developers and edge computing specialists who wish 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.
Read more...

Fine-Tuning Vision-Language Models (VLMs)

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at advanced-level computer vision engineers and AI developers who wish to fine-tune VLMs such as CLIP and Flamingo to improve performance on industry-specific visual-text tasks.By the end of this training, participants will be able to:
  • Understand the architecture and pretraining methods of vision-language models.
  • Fine-tune VLMs for classification, retrieval, captioning, or multimodal QA.
  • Prepare datasets and apply PEFT strategies to reduce resource usage.
  • Evaluate and deploy customized VLMs in production environments.
Read more...

Safety and Bias Mitigation in Fine-Tuned Models

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at intermediate-level ML engineers and AI compliance professionals who wish to identify, evaluate, and reduce safety risks and biases in fine-tuned language models.By the end of this training, 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.
Read more...

Fine-Tuning for Retrieval-Augmented Generation (RAG) Systems

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at intermediate-level NLP engineers and knowledge management teams who wish to fine-tune RAG pipelines to enhance performance in question answering, enterprise search, and summarization use cases.By the end of this training, participants will be able to:
  • Understand the architecture and workflow of RAG systems.
  • Fine-tune retriever and generator components for domain-specific data.
  • Evaluate RAG performance and apply improvements through PEFT techniques.
  • Deploy optimized RAG systems for internal or production use.
Read more...

Fine-Tuning Open-Source LLMs (LLaMA, Mistral, Qwen, etc.)

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at intermediate-level ML practitioners and AI developers who wish to fine-tune and deploy open-weight models like LLaMA, Mistral, and Qwen for specific business or internal applications.By the end of this training, participants will be able to:
  • Understand the ecosystem and differences between open-source LLMs.
  • Prepare datasets and fine-tuning configurations for models like LLaMA, Mistral, and Qwen.
  • Execute fine-tuning pipelines using Hugging Face Transformers and PEFT.
  • Evaluate, save, and deploy fine-tuned models in secure environments.
Read more...

Parameter-Efficient Fine-Tuning (PEFT) Techniques for LLMs

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at intermediate-level data scientists and AI engineers who wish to fine-tune large language models more affordably and efficiently using methods like LoRA, Adapter Tuning, and Prefix Tuning.By the end of this training, participants will be able to:
  • Understand the theory behind parameter-efficient fine-tuning approaches.
  • Implement LoRA, Adapter Tuning, and Prefix Tuning using Hugging Face PEFT.
  • Compare performance and cost trade-offs of PEFT methods vs. full fine-tuning.
  • Deploy and scale fine-tuned LLMs with reduced compute and storage requirements.
Read more...

Fine-Tuning Large Language Models Using QLoRA

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at intermediate-level to advanced-level machine learning engineers, AI developers, and data scientists who wish to learn how to use QLoRA to efficiently fine-tune large models for specific tasks and customizations.By the end of this training, participants will be able to:
  • Understand the theory behind QLoRA and quantization techniques for LLMs.
  • Implement QLoRA in fine-tuning large language models for domain-specific applications.
  • Optimize fine-tuning performance on limited computational resources using quantization.
  • Deploy and evaluate fine-tuned models in real-world applications efficiently.
Read more...

Fine-Tuning with Reinforcement Learning from Human Feedback (RLHF)

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at advanced-level machine learning engineers and AI researchers who wish to apply RLHF to fine-tune large AI models for superior performance, safety, and alignment.By the end of this training, participants will be able to:
  • Understand the theoretical foundations of RLHF and why it is essential in modern AI development.
  • Implement reward models based on human feedback to guide reinforcement learning processes.
  • Fine-tune large language models using RLHF techniques to align outputs with human preferences.
  • Apply best practices for scaling RLHF workflows for production-grade AI systems.
Read more...

Domain-Specific Fine-Tuning for Finance

 21 Hours
This instructor-led, live training in Erbil (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.
Read more...

Troubleshooting Fine-Tuning Challenges

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at advanced-level professionals who wish to refine their skills in diagnosing and solving fine-tuning challenges for machine learning models. By the end of this training, participants will be able to:
  • Diagnose issues like overfitting, underfitting, and data imbalance.
  • Implement strategies to improve model convergence.
  • Optimize fine-tuning pipelines for better performance.
  • Debug training processes using practical tools and techniques.
Read more...

Optimizing Large Models for Cost-Effective Fine-Tuning

 21 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at advanced-level professionals who wish to master techniques for optimizing large models for cost-effective fine-tuning in real-world scenarios. By the end of this training, participants will be able to:
  • Understand the challenges of fine-tuning large models.
  • Apply distributed training techniques to large models.
  • Leverage model quantization and pruning for efficiency.
  • Optimize hardware utilization for fine-tuning tasks.
  • Deploy fine-tuned models effectively in production environments.
Read more...

Prompt Engineering and Few-Shot Fine-Tuning

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at intermediate-level professionals who wish to leverage the power of prompt engineering and few-shot learning to optimize LLM performance for real-world applications. By the end of this training, participants will be able to:
  • Understand the principles of prompt engineering and few-shot learning.
  • Design effective prompts for various NLP tasks.
  • Leverage few-shot techniques to adapt LLMs with minimal data.
  • Optimize LLM performance for practical applications.
Read more...

Fine-Tuning Multimodal Models

 28 Hours
This instructor-led, live training in Erbil (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.
Read more...

Fine-Tuning DeepSeek LLM for Custom AI Models

 21 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at 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. By the end of this training, participants will be able to:
  • Understand the architecture and capabilities of DeepSeek models, including DeepSeek-R1 and DeepSeek-V3.
  • Prepare datasets and preprocess data for fine-tuning.
  • Fine-tune DeepSeek LLM for domain-specific applications.
  • Optimize and deploy fine-tuned models efficiently.
Read more...

Deploying Fine-Tuned Models in Production

 21 Hours
This instructor-led, live training in Erbil (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.
Read more...

Advanced Techniques in Transfer Learning

 14 Hours
This instructor-led, live training in Erbil (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.
Read more...

Introduction to Transfer Learning

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at beginner-level to intermediate-level machine learning professionals who wish to understand and apply transfer learning techniques to improve efficiency and performance in AI projects. By the end of this training, participants will be able to:
  • Understand the core concepts and benefits of transfer learning.
  • Explore popular pre-trained models and their applications.
  • Perform fine-tuning of pre-trained models for custom tasks.
  • Apply transfer learning to solve real-world problems in NLP and computer vision.
Read more...

Efficient Fine-Tuning with Low-Rank Adaptation (LoRA)

 14 Hours
This instructor-led, live training in Erbil (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.
  • Optimize fine-tuning for resource-constrained environments.
  • Evaluate and deploy LoRA-tuned models for practical applications.
Read more...

Fine-Tuning Models and Large Language Models (LLMs)

 14 Hours
This instructor-led, live training in Erbil (online or onsite) is aimed at intermediate-level to advanced-level 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.
Read more...

Fine-Tuning for Natural Language Processing (NLP)

 21 Hours
This instructor-led, live training in Erbil (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.
Read more...

Last Updated:

Upcoming Courses

Fine-Tuning Vision-Language Models (VLMs)

2025-07-08 09:30
14 hours
Erbil Rotana

Fine-Tuning for Retrieval-Augmented Generation (RAG) Systems

2025-07-22 09:30
14 hours
Erbil Rotana

Fine-Tuning AI for Financial Services: Risk Prediction and Fraud Detection

2025-08-05 09:30
14 hours
Erbil Rotana

Fine-Tuning for Natural Language Processing (NLP)

2025-08-19 09:30
21 hours
Erbil Rotana

Fine-Tuning Multimodal Models

2025-09-02 09:30
28 hours
Erbil Rotana

Other regions in Oman

Other Countries

These courses are also available in other countries
Online Fine-Tuning training in Erbil, Fine-Tuning training courses in Erbil, Weekend Fine-Tuning courses in Erbil, Evening Fine-Tuning training in Erbil, Fine-Tuning instructor-led in Erbil, Weekend Fine-Tuning training in Erbil, Fine-Tuning coaching in Erbil, Fine-Tuning on-site in Erbil, Fine-Tuning one on one training in Erbil, Evening Fine-Tuning courses in Erbil, Fine-Tuning private courses in Erbil, Fine-Tuning instructor in Erbil, Fine-Tuning classes in Erbil, Fine-Tuning trainer in Erbil, Online Fine-Tuning training in Erbil, Fine-Tuning boot camp in Erbil, Fine-Tuning instructor-led in Erbil