Reinforcement Learning for Real-World Applications
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Course Overview
Workshop Registration End Date :2025-02-07
Program Syllabus
Module 1
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.
Module 2
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.
Module 3
Workshop Objectives
Lead Instructor
Dr. Sarah Chen
PhD in Computational Mechanics from MIT with 15+ years of experience in Industrial AI. Former Lead Data Scientist at Tesla and current advisor to Fortune 500 manufacturing firms.
Limited SeatsClosing Soon
Reinforcement Learning for Real-World Applications
Professional Certification Program
🎥
FormatLive + Recorded
📅
Duration8 Weeks
📜
CertificationVerified
- 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.
Module 4
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
Module 5
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
Module 6
Important Dates
Module 7
Registration Ends
2025-02-07
Indian Standard Timing 3:00 PM
Module 8
Workshop Dates
2025-02-07 to 2025-02-09
Indian Standard Timing 5 : 30 PM
Module 9
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. 🚀
Module 10
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Mentor Profile
Dr. Galiveeti Poornima
Assistant Professor
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 . . .
Module 11
We are excited to announce that we now accept payments in over 20 global currencies, in addition to USD. Check out our list to see if your preferred currency is supported. Enjoy the convenience and flexibility of paying in your local currency!
List of Currencies
Fee Structure
Module 12
Student
INR. 1999
USD. 45
Module 13
Ph.D. Scholar / Researcher
INR. 2499
USD. 50
Module 14
Academician / Faculty
INR. 2999
USD. 55
Module 15
Industry Professional
INR. 4999
USD. 75
List of Currencies
Module 16
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Key Takeaways
- Access to Live Lectures
- Access to Recorded Sessions
- e-Certificate
- Query Solving Post Workshop
Module 17
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
Module 18
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
Module 21
Enter the Hall of Fame!
Take your research to the next level!
Publication Opportunity
Potentially earn a place in our coveted Hall of Fame.
Centre of Excellence
Join the esteemed Centre of Excellence.
Networking and Learning
Network with industry leaders, access ongoing learning opportunities.
Hall of Fame
Get your groundbreaking work considered for publication in a prestigious Open Access Journal (worth ₹20,000/USD 1,000).
Achieve excellence and solidify your reputation among the elite!
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Module 22
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