Executive Development Programme in Reinforcement Learning Concepts: Smart

-- ViewingNow

The Executive Development Programme in Reinforcement Learning Concepts is a cutting-edge smart certificate course designed to equip learners with essential skills in reinforcement learning. This programme is crucial for professionals seeking to stay ahead in the rapidly evolving field of artificial intelligence.

4.5
Based on 4,222 reviews

7,103+

Students enrolled

GBP £ 140

GBP £ 202

Save 44% with our special offer

Start Now

이 과정에 대해

Reinforcement learning concepts are increasingly in demand as organizations strive to create smarter, more efficient systems. This course provides a comprehensive understanding of reinforcement learning algorithms, model-free and model-based methods, and deep reinforcement learning. Learners will gain hands-on experience with popular reinforcement learning tools and frameworks. By completing this programme, learners will be able to apply reinforcement learning concepts to real-world business problems, improving decision-making and driving innovation. This course is an excellent opportunity for career advancement, providing learners with the skills needed to excel in roles such as machine learning engineer, data scientist, or artificial intelligence specialist.

100% 온라인

어디서든 학습

공유 가능한 인증서

LinkedIn 프로필에 추가

완료까지 2개월

주 2-3시간

언제든 시작

대기 기간 없음

과정 세부사항

• Introduction to Reinforcement Learning – concepts, history, and applications
• Multi-armed Bandits – algorithms, exploration vs exploitation, upper confidence bound
• Dynamic Programming – value iteration, policy iteration, Bellman equation
• Temporal Difference Learning – SARSA, Q-learning, deep Q-networks
• Model-free vs Model-based RL – advantages, disadvantages, use cases
• Function Approximation – neural networks, deep learning, linear functions
• Policy Gradients – REINFORCE, actor-critic, Proximal Policy Optimization
• Deep Reinforcement Learning – Deep Q-Networks, Dueling DQN, Rainbow
• Applications of RL – robotics, gaming, autonomous systems, recommendation systems
• Ethics in Reinforcement Learning – fairness, transparency, explainability, safety

경력 경로

SSB Logo

4.8
새 등록
→ 과정 보기