Sebastian Raschka Drops Reasoning Course

This is one of the clearest hands-on introductions to modern reasoning-model training, connecting research concepts to runnable implementations.

• –Starts from a pretrained Qwen3 0.6B model, keeping the focus on reasoning methods rather than foundation-model pretraining
• –Demonstrates verifiers, MATH-500 evaluation, self-consistency, self-refinement, and inference-time compute tradeoffs
• –Implements simplified GRPO and RLVR workflows while exposing practical issues such as reward hacking, KL terms, and training stability
• –Shows distillation from DeepSeek R1 as a complementary path to training small reasoning models
• –Early lessons can run on CPU, but later reinforcement-learning experiments are substantially more practical with a GPU