Question 1

Is the Open Source AI Academy free?

Accepted Answer

Yes, 100% free. No sign-up, no credit card. All 15 modules, 18 lessons, and 45 quiz questions are accessible immediately. Your progress saves locally in your browser.

Question 2

What topics does the Open Source AI Academy cover?

Accepted Answer

The course covers Transformer architecture, Meta Llama 4, Mistral, DeepSeek, Qwen, Gemma, Hugging Face, quantization (GGUF, AWQ, GPTQ, EXL2), Ollama, llama.cpp, vLLM, SGLang, LoRA/QLoRA fine-tuning, pre-training from scratch, RLHF/DPO/GRPO alignment, and production MLOps with Docker and Kubernetes.

Question 3

What is vLLM?

Accepted Answer

vLLM is the industry-standard engine for high-throughput production LLM serving. It uses PagedAttention for efficient GPU memory management and continuous batching for >90% GPU utilization.

Question 4

Do I need expensive hardware to run open-source models?

Accepted Answer

No. Many models can run on consumer GPUs (e.g., RTX 4090) or even CPUs via llama.cpp. The course covers deployment strategies for every budget, from Raspberry Pi edge devices to multi-GPU production clusters.

Algorithm	Library	Used By
BPE (Byte Pair Encoding)	HF tokenizers, Tiktoken	GPT-4, Llama 3/4, most models
SentencePiece	sentencepiece	Multilingual models
FlashTokenizer	Custom C++/GPU	Emerging high-speed option

Dataset	Size	Key Feature
Common Corpus	~2T tokens	Largest truly open, copyright-compliant
RefinedWeb	~5T tokens	Aggressive dedup & filtering
The Pile	825GB	22 diverse sources (books, code, papers)
RedPajama v2	30T tokens	Massive Common Crawl aggregation

Pre-Training & Tokenization

Training an LLM From Scratch

Tokenizer Selection

Pre-Training Datasets (2026)