Policy Gradients
If you like applying Policy Gradients, every challenge here gives you a chance to practice it on a real industry brief.
- ResearchAdvancedNew
Policy-Gradient Trading Agent on Historical Data
You receive 5 years of daily OHLCV (Open/High/Low/Close/Volume) data for 5 large-cap stocks. Build an episodic environment where each episode is one calendar year and the agent'…
- Policy Gradients
- Reinforce
- Rl Evaluation
Reinforcement Learning - ResearchAdvancedNew
Tune a PPO Policy for an Energy-Storage Trading Bot
You receive 18 months of 15-minute Nordic spot-price data, a battery dynamics model (capacity, round-trip efficiency, degradation curve), and a rule-based baseline that earns ab…
- Policy Gradients
- Ppo
- Reinforcement Learning
Deep Reinforcement Learning
How it works
From brief to credential, in six steps.
Step 01
Browse challenges aligned to your studies.
Step 02
Accept the one that fits your goals.
Step 03
Work through it with AI Copilot guidance.
Step 04
Submit for structured evaluation.
Step 05
Earn a verified credential.
Step 06
Add it to LinkedIn with one click.
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