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
- Overview of Reinforcement Learning (RL)
- RL Application
- Introduction to Sequential Decision
- Markov Decision Process (MDP)
- RL Algorithm Components
- Types of RL Algorithm
- Exploration & Exploitation
Day 2: Reinforcement Learning Algorithms
- A Taxonomy of RL Algorithm
- Q-Learning Algorithm
- Examples for Q-Learning Algorithm
- Advantage & Limitation of Q-Learning
- Deep Q-Network (DQN) Algorithm
- Examples for DQN Algorithm
- Deep NN Process
- Exploration & Exploitation Balancing
Day 3: RL Application and simulation
Intended For
- 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
- By the end of this workshop, participants will:
- Understand RL Fundamentals – Learn MDP, RL algorithms, and decision-making strategies.
- Implement RL Algorithms – Apply Q-Learning, DQN, and policy-based methods.
- Gain Hands-on Experience – Work with OpenAI Gym, NS3-Gym, and Python simulations.
- Explore Real-World Applications – Use RL in robotics, finance, healthcare, and gaming.
- Optimize RL Models – Balance exploration vs. exploitation for performance improvement.
- Advance Career in AI – Acquire skills for AI, automation, and intelligent systems roles.
Participants will leave equipped to build and implement RL models in real-world scenarios. 🚀
Mentor Profile
Designation: Assistant Professor
Affiliation: Presidency University, Bengaluru, SJCIT , Chikkabalapur, IIITB, Bengaluru
Dr. Galiveeti Poornima is a distinguished academician and researcher specializing in Machine Learning (ML) and Deep Learning. With a Ph.D. in Computer Science from Presidency University, Bengaluru, she has devoted her research to pioneering advancements in Signed Language Recognition, particularly for Indian Sign Languages. Her expertise extends to the application of ML and AI in healthcare, IoT, and cybersecurity, where she has contributed significantly to the development of intelligent systems for medical diagnostics and social media analytics.
Fee Structure
List of Currencies
FOR QUERIES, FEEDBACK OR ASSISTANCE
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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