Reinforcement Learning for Real-World Applications
Mastering Reinforcement Learning to Solve Complex Real-World Challenges.
Virtual (Google Meet)
Mentor Based
Moderate
3 Days
7 -February -2025
5 : 30 PM IST
About
This workshop provides an in-depth understanding of Reinforcement Learning (RL), one of the most dynamic fields in Artificial Intelligence. Participants will explore foundational concepts, advanced techniques, and hands-on projects that demonstrate the application of RL in solving practical problems. From robotics to finance, this program covers how RL can optimize decision-making and automate complex systems effectively.
Aim
To equip participants with the knowledge and skills to design, train, and deploy reinforcement learning (RL) algorithms for solving real-world problems across diverse industries.
Workshop Objectives
- To introduce participants to foundational and advanced reinforcement learning techniques.
- To enable participants to design, train, and evaluate RL algorithms.
- To explore diverse applications of RL in industries like robotics, healthcare, and finance.
- To emphasize ethical and practical considerations in RL deployments.
- To prepare participants for research and professional roles in RL and AI-driven systems.
Workshop Structure
Day 1: Foundations of Reinforcement Learning
-
- Understanding the Basics: Agents, Environments, Rewards, and Actions
- Key Algorithms: Q-Learning, SARSA, and Deep Q-Networks (DQN)
- Exploration vs. Exploitation: Balancing Strategies
- Case Studies: Reinforcement Learning in Game Playing (e.g., AlphaGo)
- Interactive Session: Simulating Simple RL Problems
Day 2: Advanced Techniques and Optimization in Reinforcement Learning
-
- Policy Gradient Methods: REINFORCE, PPO, and Actor-Critic Models
- Enhancing Efficiency: Experience Replay, Prioritized Sampling, and Transfer Learning
- Hands-On Workshop: Training RL Models for Real-Time Decision Making
- Discussion: Challenges in RL, such as Stability, Convergence, and Scalability
Day 3: Real-World Applications of Reinforcement Learning
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- Applications in Robotics: Path Planning and Control Systems
- RL in Finance: Portfolio Management and Algorithmic Trading
- Applications in Healthcare: Personalized Treatments and Drug Discovery
- Ethical and Practical Considerations: Risk Management in RL Deployment
- Panel Discussion: The Future of RL in Real-World Applications
Participant’s Eligibility
- AI and machine learning professionals
- Students and researchers in computer science, robotics, and AI
- Professionals in industries such as finance, healthcare, and automation
- Enthusiasts interested in applying RL to real-world challenges
Important Dates
Registration Ends
2025-02-07
Indian Standard Timing 3:00 PM
Workshop Dates
2025-02-07 to 2025-02-09
Indian Standard Timing 5 : 30 PM
Workshop Outcomes
- Comprehensive understanding of RL principles and algorithms
- Proficiency in implementing RL solutions for real-world scenarios
- Hands-on experience with state-of-the-art RL tools and frameworks
- Awareness of ethical considerations and challenges in RL applications
- Insights into future trends and research directions in reinforcement learning
Fee Structure
Student
INR. 1999
USD. 45
Ph.D. Scholar / Researcher
INR. 2499
USD. 50
Academician / Faculty
INR. 2999
USD. 55
Industry Professional
INR. 4999
USD. 75
List of Currencies
Key Takeaways
- Access to Live Lectures
- Access to Recorded Sessions
- e-Certificate
- Query Solving Post Workshop
Future Career Prospects
- Reinforcement Learning Engineer
- AI Specialist in Robotics
- Data Scientist for Autonomous Systems
- Research Scientist in RL and AI Optimization
- Algorithm Developer for Smart Systems
Job Opportunities
- RL Engineer in Gaming or Simulation Development
- Robotics Control Engineer
- AI Researcher in Finance or Healthcare Applications
- Optimization Specialist in Supply Chain and Operations
- Autonomous Vehicle System Developer
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great knowledge about topic.