# RL 101: Native Reinforcement Learning & Post-Training (HARLE) — Hanzo University > Implement native Gymnasium environments on the Hanzo Cloud Fabric. Fine-tune models with Zoo Gym, design multi-objective reward functions, and train learned routing policies. Earn your HARLE credential with 25% compute credit rebate and isolated gVisor sandboxes. [Models](https://hanzo.ai/models)/RL 101: Native Reinforcement Learning & Post-Training Course RL 101 · Units: 5.0 · Credential: HARLE # Native Reinforcement Learning & Post-Training Implement native Gymnasium environments on the Hanzo Cloud Fabric. Fine-tune models with Zoo Gym, design multi-objective reward functions, and train learned routing policies. [Enroll in RL 101 — $249 USD (+$63 Credit Rebate)](https://hanzo.ai/pay/cart?plan=course-rl-101&returnUrl=https%3A%2F%2Fhanzo.ai%2Funiversity%2Freinforcement-learning)[Preview Enrolled Student Portal →](https://hanzo.ai/university/portal) Academic specificationsRL 101 · 5.0 UNITS Duration5 Weeks · Advanced Lab LEVELExpert CredentialHARLE Credential formatW3C Verifiable Credential Lead Faculty & Academic Direction Dr. Mira ThorneHead of Alignment & RL Research, Hanzo Labs PrerequisitesFoundational linear algebra, Python ML libraries, and basic MDP comprehension Tuition & compute rebateOpen enrollment Total tuition$249USD +$63 CREDITS (25% REBATE) Guaranteed compute allocation deposited immediately on enrollment. Subsidizes Zen 6 inference and gVisor sandbox runtimes. [Enroll in RL 101 — $249 USD →](https://hanzo.ai/pay/cart?plan=course-rl-101&returnUrl=https%3A%2F%2Fhanzo.ai%2Funiversity%2Freinforcement-learning)Have a coupon code or fellowship grant? Enter it during checkout. Automatic 25% Compute Credit Rebate 25% of tuition (rounded up) is immediately deposited into your Hanzo Cloud compute balance on day one. Fully subsidizes your gVisor sandbox container leases and model inference throughout the course. Already purchased?[Enter Enrolled Student Portal →](https://hanzo.ai/university/portal) Competency Framework ## What you master in RL 101 Engineered for software practitioners building resilient autonomous production systems. Gymnasium HanzoAgentEnv MDP implementation Post-training & fine-tuning with Zoo Gym Multi-objective reward modeling (PPO, GRPO, DPO) LinUCB router policy training via /v1/ai/feedback Comprehensive Syllabus ## Curriculum & Laboratory Breakdown Every module combines systems architecture lectures with hands-on containerized lab defense. RL 101.1Markov Decision Processes for Code & Tool Agents Week 1 Formalize tool invocation and multi-step reasoning as discrete-action Markov Decision Processes.Key Topics & Lectures: MDP formulation: state spaces, action observation histories, and transition kernels Tool execution environments: defining episodic boundaries and termination predicates Discount factors, horizon truncation, and sparse vs dense reward landscapes Assigned Readings: Sutton & Barto: Reinforcement Learning: An Introduction (Chapters 3-4) Lab 1: Wrap the Hanzo Tool API into a compliant Gymnasium environment with observation spaces. RL 101.2Reward Engineering: Multi-Objective & Process Supervision Week 2 Construct robust reward models that prevent reward hacking, verbosity bloat, and hallucinated proofs.Key Topics & Lectures: Outcome vs process supervision: step-level scoring versus terminal exit code reward Regularization penalties: token cost budgets, execution latency, and safety constraints Training preference models with Direct Preference Optimization (DPO) and KTO Assigned Readings: Rafailov et al.: Direct Preference Optimization: Your Language Model is Secretly a Reward Model Lab 2: Implement a multi-objective reward function incorporating test exit code, latency, and cost. RL 101.3Policy Gradient Optimization: PPO & GRPO at Scale Week 3 Train open weights models using Proximal Policy Optimization and Group Relative Policy Optimization.Key Topics & Lectures: PPO actor-critic architectures and clipping dynamics GRPO: group relative advantages without dedicated critic networks Distributed rollout collection across vLLM and TensorRT-LLM nodes Assigned Readings: Schulman et al.: Proximal Policy Optimization Algorithms DeepSeek-AI: DeepSeekMath & GRPO Lab 3: Execute a 1,000-step GRPO fine-tuning loop on Zen 6 Flash for multi-hop tool routing. RL 101.4Contextual Bandits & Learned Model Routers Week 4 Deploy real-time contextual bandit policies (LinUCB, Thompson Sampling) for dynamic model tiering.Key Topics & Lectures: Exploration vs exploitation in production request dispatch Feature vectors: prompt complexity, token count, task classification, and latency requirements Streaming updates via POST /v1/ai/feedback and counterfactual regret minimization Assigned Readings: Li et al.: A Contextual-Bandit Approach to Personalized News Article Recommendation Lab 4: Deploy a real-time LinUCB router dispatching requests between Zen 6 Flash and Zen 6 27B. RL 101.5Production Evaluation, Safety & Capstone Defense Week 5 Evaluate trained policies on unseen benchmark suites, verify safety bounds, and defend the capstone.Key Topics & Lectures: Out-of-distribution generalization testing and catastrophic forgetting mitigation Safety guardrail integration and automated adversarial red-teaming Issuance of HARLE W3C Verifiable Credentials Assigned Readings: Anthropic: Sleeper Agents & Out-of-Distribution Robustness Capstone Defense: Train and deploy a custom MDP router achieving 92% benchmark accuracy at 40% lower cost. Final Examination ## Capstone Defense & Credential Issuance Train a custom MDP reinforcement learning policy and deploy it as a production model router. Upon automated grading verification, your HARLE W3C Verifiable Credential is cryptographically signed and issued to your Hanzo DID. [Enroll in RL 101 — $249](https://hanzo.ai/pay/cart?plan=course-rl-101&returnUrl=https%3A%2F%2Fhanzo.ai%2Funiversity%2Freinforcement-learning)[Preview Student Portal](https://hanzo.ai/university/portal) Hanzo University Tracks ## Explore the Complete Curriculum Six specialized engineering credentials designed for the frontier of autonomous intelligence. ENG 100HACE Agentic Coding Systems with Hanzo Dev & Zen 6Architect autonomous coding agents capable of multi-file refactoring, test-driven debugging, and opening verified pull requests using Zen 6, ZAP RPC, and isolated gVisor sandboxes. $199 USD[View Course →](https://hanzo.ai/university/agentic-coding) RL 101HARLE Native Reinforcement Learning & Post-TrainingImplement native Gymnasium environments on the Hanzo Cloud Fabric. Fine-tune models with Zoo Gym, design multi-objective reward functions, and train learned routing policies. $249 USD[View Course →](https://hanzo.ai/university/reinforcement-learning) SYS 103HCAISE Hanzo AI Systems Engineering FoundationThe definitive engineering standard for production AI. Master the 4-surface parity, finite-state Kai decision loops, hybrid retrieval, and strict integer micro-USD budget governance. $149 USD[View Course →](https://hanzo.ai/university/systems-engineering)