The Java programming language is a vital part of delivering new information that helps people connect and businesses grow.
This language connects applications to data, data with people and people with their digital lifestyle and is used by more than 12 million programmers worldwide.
From artificial intelligence and machine learning to blockchain and more, let's explore the sectors in which Java is used today and will continue to play an integral role in the future.
Artificial intelligence (AI) and machine learning are key components of the development of digital transformation that is currently taking place around the world. Many things are happening in this sector as organizations find ways to use these technologies to make better business and operational decisions.
Artificial intelligence is a broad term that refers to systems designed to perform actions that are usually performed by humans and that mimic human intelligence. With machine learning, instead of being programmed to perform a set of steps, the machine can access algorithms that analyze data and then use that data to control the tasks it performs.
To clear up the confusion, this blog includes some useful definitions of overlapping terms. It claims that AI means making a computer mimic human behavior, while machine learning is a set of techniques and algorithms that allow computers to figure things out from data and deliver AI applications.
Many developers working in AI find Java a good choice as a language to use in their projects. Recently, a consulting firm said the following about using Java for AI: "No language can offer you the ideal value of your time and effort, but Java seeks perfection." AI programming in Java has more benefits than disadvantages, so you can use it securely to develop smart products.
Some of the benefits of Java are that the language is easy to learn, widely used and understood by thousands of developers, and is a good language for encoding the algorithms that form the basis of AI. In addition, Java scales well and is object-oriented.
Open source AI libraries are available to help developers who plan to use Java for AI projects. This article lists some of the popular Java AI libraries for machine learning, neural networks, natural language processing, and more.
A subset of AI, machine learning involves creating systems that learn (or improve performance) based on the data they process. Algorithm-driven machine learning forms the basis of new developments with autonomous cars and facial recognition software.
Why do Java developers care about this? A JavaWorld article had this to say. "As a Java developer, you want to get ahead of this curve now, when tech companies are starting to invest seriously in machine learning. What you learn today, can be developed over the next five years, but you have to start somewhere."
A popular machine learning platform is Waikato Environment for Knowledge Analysis (Weka), which was developed by Waikato University, New Zealand. It is written in Java and provides a graphical user interface, a command-line interface, and a Java API. It is a popular Java machine learning library and a useful tool for machine learning projects.
Weka includes a set of visualization tools and algorithms for data analysis and predictive modeling, as well as graphical user interfaces to access these functions. Weka is portable because it is fully implemented in Java, so it can run on almost any computing platform.
The reasons why a data scientist or developer chooses a programming language can be a personal preference or your organization's culture choice. While many languages are used with Big Data, Java is often front and center to use these tasks.
An InfoWorld article on programming languages for big data projects explains why Java is a good choice. "Consider Hadoop MapReduce - Java. HDFS? Written in Java. Even Storm, Kafka, and Spark run on JVM (on Clojure and Scala), which means Java is a first-class citizen of these projects. . . . using Java gives you access to a large ecosystem of profilers, debuggers, monitoring tools, libraries for enterprise security and interoperability, and more, most of which have been tested in battle over the past two decades."
Another article in Jaxenter says that although Python and R are widely used, Java is a great language for big data projects. The author, Aaron Lazar, lists 10 reasons to use Java, including this: Java is one of the oldest languages used for business development and it is quite likely that the organization you are working on also has an important part of your Java-based infrastructure: 10 reasons why data scientists need to learn Java from Jaxenter.com. To do this, you may want to prototype in R or Python and then rewrite your models in Java.
Blockchain allows organizations to agree on a unique and distributed source of truth. With blockchain, unalterable records (blocks) are linked to form a chain and distributed securely among participants. It allows transactions over a network and guarantees the integrity and validity of those transactions. This Oracle blog explains more about blockchain technology, and here's another easy-to-follow explanation that's an excerpt from Omid Malekan's book The Story of Blockchain.While Oracle offers a blockchain platform, some developers may want to use Java to develop or customize blockchain applications. Here are some useful resources to explore:
Blockchain implementation with Java code. This DZone article provides examples of blockchain implementations with Java and includes code samples.
Creating your first blockchain with Java. A set of Medium articles form a series of tutorials that show how Java can be used to develop blockchain technology.
Creating your first blockchain with Java code. This article, published on the Influential site, provides a good explanation of three types of blockchain (public, federated, and private) along with some examples of using Java code to configure a block.
Popular languages like Java, C++, C#, and Python see developers write object-oriented code. For many new developers, the paradigms of object-orientation present new ways of thinking that are difficult to grasp conceptually. But they're fundamental to becoming a software engineer.
Game-Based Learning
Oracle's Java Puzzle Ball game is a powerful tool to build your understanding of key programming concepts: class design, static vs. instance variables, inheritance, and lambda expressions Java. Puzzle Ball is part of a course that utilizes a game-based learning methodology.
Playing the game builds your conceptual understanding and makes technical lecture content much easier to absorb. This should also translate to better performance and problem-solving ability in the programming labs.
We've saved all the old versions of Java Puzzle Ball so you can explore how features were gradually implemented and get insight into the software development process.
Game Developer Skills
Games are software. If you're a game developer, there's great benefit to building and enhancing your programming skills. The topics discussed in Oracle University's Java curriculum should be invaluable to all types of software engineers.