Language Model Development
Build, train, and scale modern LLMs.
Customized corporate training designed for engineering teams in 2026. Master the full lifecycle—from model internals to industrial deployment.
Get a Corporate Proposal →Who Is This Program For?
Engineers Building Modern LLM Systems
Engineers who want a complete, end-to-end understanding of LLM development - from Transformers and pretraining to fine-tuning, PEFT, RAG, agents, multimodality, and LLMOps.
Developers Moving Beyond "Prompting Only"
Developers who want to learn fine-tuning, LoRA/QLoRA, evaluation, alignment, RAG workflows, and structured LLM application design.
Data Scientists Specializing in LLM Workflows
Data scientists who want mastery of tokenization, dataset curation, evaluation, RAG pipelines, vector DBs, re-ranking, and performance monitoring.
AI Professionals Designing Agents and LLMOps
Professionals who want to build agentic workflows, guardrails, MLSecOps, monitoring, and production-ready LLM systems.
Advanced LLM Curriculum
Industrial LLM Development
Production-Ready LLMs
Move beyond notebooks. Understand Transformer internals, Self-Attention, and RAG pipelines to build language tools that serve users at industrial scale.
Deployment & Lifecycle
Solve engineering challenges: mixed-precision training, model versioning with ONNX/TorchScript, and deploying via FastAPI endpoints.
Enterprise Delivery Options
| Format | Language & Scale | Business Objective |
|---|---|---|
| Individual Self-Paced | English / Hebrew | Foundational training for engineers moving into generative AI. |
| Corporate Live Frontal | Worldwide Delivery | Intensive team upskilling delivered onsite at your workspace. |
| Corporate Online Live | English / Hebrew | Interactive remote sessions for distributed dev departments. |
| Corporate Hybrid | Customized | Blended programs combining recorded theory with live labs. |
Industrial LLM Development
A technical deep-dive into how 2026 language models are architected, optimized, and deployed in production-ready engineering environments.
What You’ll Gain
Deep Understanding of LLM Foundations
Master the core concepts behind modern language models - tokenization, embeddings, attention, Transformer blocks, scaling laws, and the ecosystem of LLMs and SLMs.
Practical Training in Pretraining & Fine-Tuning
Learn how models are pretrained at scale and how to adapt them using full fine-tuning or PEFT methods such as LoRA, QLoRA, DoRA, and VeRA - with hands-on exercises.
Real-World LLM Systems & Retrieval
Implement retrieval-augmented generation (RAG), vector databases, re-ranking, query planning, evaluation (EvalOps), and the foundations of agentic AI workflows.
Production-Ready LLMOps Skills
Build deployable LLM systems with guardrails, monitoring, safety, MLSecOps, compliance, and scalable infrastructure - skills needed for real enterprise-grade AI.