Learning with reinforcement in Java
The training provides a practical introduction to implementing reinforcement learning algorithms in Java. The workshop program combines fundamental machine learning theory with intensive hands-on exercises, enabling participants to understand and implement learning systems based on interactions with the environment. The class focuses on practical applications, using real-world scenarios and examples of Java implementations.
Issues
-
Foundations of teaching with reinforcement
-
Q-learning and SARSA algorithms
-
Policy Gradient Methods
-
Implementation of agents
-
Simulation environments
-
Multi-agent Systems
-
Transfer Learning
-
Algorithm optimization
-
Recommendation systems
-
Robotics and control
-
Testing AI systems
-
Integration with applications
Benefits
- The participant will gain a thorough knowledge of implementing reinforcement learning algorithms in Java
- To design and develop learning systems based on interactions with the environment
- The practical aspects of implementing learning agents in real applications
- Will be able to optimize and tune the parameters of learning algorithms
- Will gain the ability to integrate learning systems into existing Java applications
- Will master methods for testing and validating machine learning systems
- Will gain practical experience in implementing advanced reinforcement learning techniques
Who is this training for?
Prerequisites
- Practical knowledge of Java
- Fundamentals of mathematics and statistics
- Experience in object-oriented programming
- Basic knowledge of machine learning
Training program
Theory and mathematical foundations
- Markov decision processes
- Functions of reward and punishment
- Exploration strategies
- Implementation of algorithms
Q-learning in Java
- SARSA and Deep Q-Networks
- Implementation of agents
- Simulation environments
Advanced techniques
- Policy Gradient Methods
- Actor-Critic Architecture
Multi-agent Systems
- Transfer Learning
- Practical applications
- Process optimization
- Recommendation systems
- Robotics and control
- Games and simulations
Delivery Methods
Online
- Convenience of participating from anywhere
- Interactive live sessions with trainer
- Materials available for 30 days
- No travel costs
On-site
- Direct contact with trainer and group
- Intensive hands-on workshops
- Networking with other participants
- Full focus on learning
Frequently asked questions
Who is the Learning with reinforcement in Java training for?
This training is designed for professionals looking to develop skills in learning with reinforcement in java. Required level: beginner.
How long is the Learning with reinforcement in Java training?
The training lasts 3. Available in online or on-site format.
Will I receive a certificate?
Yes — every participant receives a completion certificate confirming acquired competencies. EITT holds ISO 9001 accreditation.
Can this training be conducted for a closed group?
Yes — we offer dedicated closed trainings for companies. We customize the program to your team's needs. Contact us for an individual quote.
Request a quote
Funding Options
Check funding options for your company
Development Services Database
Up to 80% funding for SMEs from EU funds
Check availabilityNational Training Fund
Up to 100% funding for employers
Learn moreTrusted by
We train teams at Poland's largest companies
Interested in this training?
Contact us - we'll prepare an offer tailored to your organization's needs.