Java for AnyLogic
What you'll learn
- How to build simpler, better models, faster in AnyLogic
- How to use fundamental Java concepts in simulations models built in AnyLogic
- Create more flexible and extensible simulation models in AnyLogic
- Create more advanced models in AnyLogic
- Learn tips and trips to building better models in AnyLogic
- Basic knowledge of AnyLogic
- Basic programming knowledge, preferably Java
- Some experience in simulation modeling
This course is for beginner to moderate AnyLogic users that want to learn how to use the Java programming language and Object-Oriented Programming principles to make better more efficient models faster.
The course is structured from simple topics, like variables in Java, to more complex ideas such as Class Inheritance. You will start by learning the basics of Java, then we move to more complex features like data structures, and finish by learning and implementing complex concepts such as Inheritance, polymorphism and other Java features that allow extending AnyLogic's capabilities.
AnyLogic is a powerful tool and a market leader in the simulation world, but in order to build useful and efficient models, one needs to master Java and understand its capabilities. Mastering the most common and useful Object-Oriented programming concepts and applying them will result in better, faster and more extensible models. The ability to extend a simulation package via a powerful, and industry-standard, programming language is what differentiates AnyLogic from other offers in the market.
This course is the first part of a series aimed at providing a solid Java programing skillset to AnyLogic users, in order to solve complex problems by producing more robust, extendible and reliable models.
Who this course is for:
- Beginner and moderate AnyLogic users
I am passionate about solving seemingly complex problems with simple solutions and teaching others how to do the same.
This passion has lead me to focus on using technology, especially simulation to, find, test and validate potential solutions to common business problems.
I have over a decade of experience in using simulation and other tools to provide valuable insights to clients and partners.
I work with a variety advanced analytics areas, such as agent-based modeling, machine learning or mathematical optimization. 7+ plus experience helping companies to solve complex problems and make better decisions. I am particularly interested in simulation modeling (agent-based modeling, discrete event modeling), as I think it has an enormous potential to solve complex problems that usually other approaches fail to solve or to provide reasonable solutions.