The Local Large Language Model (Local LLM) Development for Enterprise Environments training course is designed for technical professionals who want to build AI applications that meet organizational requirements for data privacy, security, and performance by deploying large language models within their own infrastructure.

The course covers local AI infrastructure planning, hardware requirements, and the selection of open-source language models. Participants learn to prototype, test, and compare models using LM Studio before moving on to building customized models with Ollama and integrating them into Python and JavaScript applications.

By the end of the program, participants will have the knowledge and practical skills needed to plan an end-to-end local AI solution that runs within enterprise infrastructure, provides API-based access, and uses internal company documents as a knowledge source.

For corporate groups, we can organize this training as an on-site private group.

Prerequisites

Participants are required to have basic Python or JavaScript programming knowledge and familiarity with command-line operations. Introductory knowledge of Docker is also recommended.

Who Should Attend

Software developers interested in building AI-powered applications and solutions
Data scientists and machine learning engineers
DevOps professionals and infrastructure engineers
Software architects and solution architects
Technical team leaders responsible for enterprise AI development projects

What You Will Learn

Upon completing this course, you will be able to:

Compare local and cloud-based large language models in terms of cost, security, and performance.
Plan local AI architectures while considering GDPR and KVKK compliance requirements.
Determine appropriate hardware capacity for enterprise AI workloads.
Evaluate open-source language models based on licensing, model size, and technical capabilities.
Test language models with LM Studio and expose OpenAI-compatible local API services.
Create customized model configurations using Ollama and Modelfile.
Integrate local LLM solutions into Python and JavaScript applications.
Configure model access and user management using Docker and Open WebUI.
Design RAG-based AI assistants that work with internal organizational documents.

Training Outline

1. Planning Local AI Infrastructure

Enterprise Strategy and Technology Selection

Comparing cloud-based and locally deployed language model architectures
Evaluating data security, privacy, and compliance requirements under GDPR and the Turkish Personal Data Protection Law (KVKK)
Analyzing token-based usage costs and the return on hardware investments

Hardware and Operating System Requirements

Capacity planning for processors, GPU memory (VRAM), and system memory (RAM)
Preparing Windows, macOS, and Linux server environments
Configuring CUDA and Metal hardware acceleration frameworks

Open-Source Language Model Ecosystem

Reviewing model licenses, sizes, and capabilities through Hugging Face model cards
Exploring the use cases of GGUF, AWQ, and EXL2 model formats
Comparing the effects of quantization techniques on model accuracy and inference speed

2. Model Prototyping and Evaluation with LM Studio

Developing local language model prototypes using LM Studio
Testing and comparing different language models
Exposing OpenAI-compatible local API endpoints

3. Enterprise Local LLM Solutions with Ollama

Creating organization-specific model configurations using Ollama and Modelfile
Managing versions of customized language models
Integrating local language models into Python and JavaScript projects
Deploying Open WebUI with Docker and managing user access
Designing RAG-based AI assistants that use internal corporate documents

Why Choose Us

Leading UK-based global training provider since 1995.

Experience Local Large Language Model (Local LLM) Development for Enterprise Environments in Changi through Bilginç IT Academy's live and interactive virtual classroom environment. Join a Public course as an individual delegate or arrange a dedicated Private / In-house online training program exclusively for your organization.

Delivery Method: Online Instructor-Led
Participation Model: Public / Private (In-house)
Live and Interactive Training: Connect with your instructor in real time and actively participate through discussions, Q&A sessions, practical exercises, and group activities.
Flexible Participation: Join the training from your home, office, or any location with a suitable internet connection.
Expert Trainer Network: Learn from experienced trainers with strong industry backgrounds and practical field expertise.
Over 30 Years of Training Expertise: Benefit from Bilginç IT Academy's professional training experience since 1995.
Worldwide Access: Join our live virtual classrooms from Changi or anywhere else in the world, or arrange a dedicated online training program for your organization.

Experience Local Large Language Model (Local LLM) Development for Enterprise Environments through face-to-face Classroom Based training in Changi. Training can be delivered as a Public course open to individual delegates or as a dedicated Private / In-house class for your organization.

Delivery Method: Classroom Based
Participation Model: Public / Private (In-house)
Face-to-Face Learning: Interact directly with your instructor and fellow delegates in an engaging classroom environment.
Experienced Trainers: Learn from specialists with extensive industry experience and practical real-world knowledge.
Professional Training Environment: Attend training in comfortable, well-equipped classrooms designed to support effective learning.
Practical Learning: Depending on the course, reinforce your knowledge through hands-on exercises, scenarios, case studies, and instructor-led activities.

Arrange Local Large Language Model (Local LLM) Development for Enterprise Environments in Changi as a dedicated Onsite training program for your organization. Bilginç IT Academy trainers can deliver the training at your office or another location of your choice, with the program planned around your team's requirements and business objectives.

Delivery Method: Onsite
Participation Model: Private (In-house)
Training at Your Preferred Location: Organize the training at your company's office or another location selected by your organization.
Tailored Course Content: Adapt the training program to your projects, team structure, existing skill levels, and specific business requirements.
Team-Focused Learning: Develop your team around a shared knowledge base while strengthening internal collaboration and knowledge transfer.
Flexible Scheduling: Plan the training dates, location, and program according to your organization's operational requirements.
Worldwide Onsite Delivery: Arrange the training in Changi or at another preferred location worldwide. Bilginç IT Academy trainers can travel to your selected location to deliver the dedicated training program.

Local Large Language Model (Local LLM) Development for Enterprise Environments Training in Changi