Deep Reinforcement Learning Course
This course teaches practical deep reinforcement learning for robotics, covering environment simulation, algorithm selection (SAC, PPO, TD3), reward design, sensor integration, safety measures, sim-to-real transfer, and deployment evaluation.
flexible workload from 4 to 360h
valid certificate in your country
What will I learn?
This Deep Reinforcement Learning Course provides a practical way to build and deploy strong RL policies for complex robotic systems. You will create simulated environments, design rewards, select algorithms like SAC, PPO, and TD3, and develop vision and sensor fusion systems. Learn to ensure safety, handle sim-to-real transfer, monitor metrics, and run reliable 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 behaviour.
- 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 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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