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AI Anytimefor Business

Open source · Platform training

Open-Source LLM & Private AI Training

For: Engineering, infrastructure and data teams in regulated or cost-sensitive organizations.

2-day workshop4-day bootcamp

In short

Open-Source LLM training teaches teams to run AI on their own infrastructure — selecting and serving open models such as Llama, Qwen, Mistral and Gemma, fine-tuning them for domain tasks, and making sound trade-offs between private and API-based AI. It's where AI Anytime's open-source roots run deepest.

What your team will be able to do

  • Choose the right open model for each use case
  • Serve models efficiently with vLLM, Ollama or TGI
  • Fine-tune with LoRA/QLoRA on domain data
  • Private RAG and agents inside your network
  • Clear cost and performance comparisons vs APIs

Capstone

Deploy a private RAG assistant on an open model inside your environment.

Tools & stack

Hugging FacevLLMOllamaUnslothPEFTDockerKubernetes

Curriculum

Program modules

A typical outline — every program is tailored to your team's roles, tools, data policies and use cases after a scoping call.

  1. 01

    Open models landscape

    • Llama, Qwen, Mistral, Gemma, DeepSeek
    • Licensing and benchmarks
    • Hugging Face ecosystem
  2. 02

    Serving

    • Quantisation and GPUs
    • vLLM, Ollama, TGI
    • Scaling and monitoring
  3. 03

    Fine-tuning

    • Data preparation
    • LoRA / QLoRA
    • Evaluation

FAQs

Open-Source & Private LLMs: frequently asked questions

Still have questions? Talk to our team — we reply within one working day.

Should we use open-source LLMs or APIs?

It depends on data sensitivity, scale, latency and team skills. Many enterprises use both. The program gives your team a framework and hands-on experience to decide.

Next step

Bring Open-Source & Private LLMs to your team.

Tell us who you want to upskill and what outcome you need. You'll get a tailored proposal — curriculum, format, trainers and pricing — within 48 hours.