Certificate in RL for Strategic Decision Making
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Course Details
• Introduction to Reinforcement Learning (RL)
• RL algorithms and environments
• Q-learning and state-action value functions
• Policy gradients and policy-based methods
• Deep reinforcement learning and neural networks
• Exploration vs Exploitation in RL
• Case studies of RL in strategic decision making
• Tools and frameworks for implementing RL algorithms
• Ethical considerations in RL and AI
Career Path
Entry Requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course Status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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