Introduction to LLMs
A beginner-friendly course covering the fundamentals of Large Language Models — what they are, how they work, and how to use them effectively.
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5 OF 5 COURSES AVAILABLE
Frontier model literacy
Engineers, researchers and analysts who want to understand how frontier models are trained, measured and aligned.
Where this path leads
Read a model release or paper critically: what training changed, what the evals really measure, and which safety claims are supported.
- Available now
Post-Training: Fine-Tuning, RLHF & DPO
How instruction tuning, preference learning and LoRA shape a model.
advanced - Available now
Reasoning Models & Test-Time Compute
Chain-of-thought, self-consistency and process supervision.
advanced - Available now
LLM Engineering: RAG, Evals & Multimodal Apps
Benchmarks, contamination and task-specific evaluation.
intermediate - Available now
AI Safety & Alignment for Builders
Alignment methods, red-teaming and human oversight.
advanced
Available courses in this path
Post-Training: Fine-Tuning, RLHF & DPO
Learn how supervised fine-tuning, RLHF, DPO, and LoRA turn a pre-trained model into an assistant, audit preference data, and decide when fine-tuning is worth it. Offline labs; no GPU required.
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Reasoning Models & Test-Time Compute
Understand chain-of-thought, test-time compute, self-consistency, and verifiers. Measure when a reasoning model is worth its cost and latency, using offline labs that need no paid API.
By Admin
Free courseView course
LLM Engineering: RAG, Evals & Multimodal Apps
Build a transparent retrieval baseline, validate citations and access, design multimodal workflows, and evaluate an evidence-based tutor prototype.
By Admin
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AI Safety & Alignment for Builders
Threat-model LLM applications, defend against direct and indirect prompt injection with controls enforced in code, handle personal data carefully, and build a red-team suite. Offline labs; no paid API.
By Admin
Free courseView course