Beginner~2h
How LLMs Are Built in LLM CoreInterview Readiness Check
The three training stages — pretraining on web-scale data, supervised fine-tuning on instructions, RLHF/DPO for alignment. What each stage produces, why it matters, what you can and can't change downstream..
pretrainingsupervised fine-tuningSFTRLHFDPOalignmentinstruction tuning
Learning path
What LLMs Actually Are→How LLMs Are Built ← you are here→Reasoning Models & Extended ThinkingPractical Fine-Tuning (LoRA, QLoRA, SFT, DPO)
Try a sample question
Your company has 500GB of internal support documents and wants to train an LLM that knows about your product domain. The team debates between pretraining from scratch vs. fine-tuning an existing model. Given a budget of $50,000, which is most appropriate?
A.Pretraining from scratch — domain specificity requires a fresh model uncontaminated by web data
B.Pretraining is always cheaper because you control the dataset size
C.Fine-tuning or continued pretraining on an existing open-source base model — far more compute-efficient and achieves domain adaptation at a fraction of the cost
D.Neither — you must use an API-based model for any custom domain
Sign up free to take the full check and see the answer with an explanation.
What this module tests
- Conceptual understanding of how llms are built fundamentals
- Trade-offs and design decisions in real system scenarios
- pretraining and supervised fine-tuning — applied knowledge
- Interview-style reasoning and explanation quality
Free to start
Take the How LLMs Are Built check →
10 questions · Dimension scoring · AI coach feedback · Shareable result
Test your knowledge — free →No credit card · Takes 10–15 min
Frequently asked questions
- What does the How LLMs Are Built check test?
- The check covers the three training stages — pretraining on web-scale data, supervised fine-tuning on instructions, rlhf/dpo for alignment. what each stage produces, why it matters, what you can and can't change downstream.. Questions span beginner to advanced difficulty and test both conceptual understanding and practical trade-off reasoning.
- What keywords should I know for How LLMs Are Built?
- Key concepts include: pretraining, supervised fine-tuning, SFT, RLHF, DPO, alignment, instruction tuning. These frequently appear in llm core interviews at product and infrastructure companies.
- How many questions are in the check?
- Each check has 10 questions — a mix of MCQ and short-answer. You get scored by dimension (e.g., scalability, consistency) so you know exactly where to focus.
- How long does it take to study How LLMs Are Built?
- Most engineers spend around 2 hours on this module. The check itself takes about 10–15 minutes. You can retake it up to 3 times per day.
- What prerequisite knowledge do I need before How LLMs Are Built?
- How LLMs Are Built builds on What LLMs Actually Are. Complete those first for the best results.
- Is pretraining, supervised fine-tuning, SFT covered?
- Yes. The How LLMs Are Built module covers pretraining, supervised fine-tuning, SFT among other key concepts. The check includes questions that reflect real llm core interview patterns.