Deep Reinforcement Learning Course
This course equips learners with hands-on skills to implement deep reinforcement learning for robotics, covering simulation, algorithm selection, reward engineering, sensor integration, and safe deployment.
from 4 to 360h flexible workload
valid certificate in your country
What will I learn?
This Deep Reinforcement Learning Course provides a practical approach to developing and implementing strong RL policies for intricate robotic setups. You will create simulated settings, design reward systems, select algorithms such as SAC, PPO, and TD3, and construct vision and sensor integration processes. Gain knowledge in ensuring safety, handling sim-to-real transitions, monitoring metrics, and executing dependable evaluation and deployment processes from start to finish.
Elevify advantages
Develop skills
- Design RL tasks for robots: define states, actions, rewards, and safety.
- Build robust sim-to-real pipelines with domain randomization and monitoring.
- Engineer rewards and penalties that drive safe, efficient robotic behavior.
- Select and tune DRL algorithms (PPO, SAC, TD3) for stable robot control.
- Configure sensors and state fusion for reliable factory-floor perception.
Suggested summary
Before starting, you can change the chapters and the workload. Choose which chapter to start with. Add or remove chapters. Increase or decrease the course workload.What our students say
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