This Specialization equips learners with the skills to design, implement, and deploy machine learning solutions using Java. Starting with core ML concepts like regression, classification, and clustering, learners will apply Java-based tools such as Weka, Smile, Tribuo, and Deeplearning4j to build real-world models. The courses cover data preprocessing, model training, evaluation, deep learning, NLP, and large-scale ML with Spark and Mahout. Learners will also explore advanced topics like federated learning and MLOps practices using Jenkins and GitHub Actions. By the end of the specialization, participants will be able to create and deploy scalable ML applications in enterprise environments with Java.
Java in Machine Learning Specialization
Discover new skills with 30% off courses from industry experts. Save now.
Java in Machine Learning Specialization
Machine Learning Development with Java. Learn to build, deploy, and scale machine learning models using Java and industry-standard tools.
Instructor: Board Infinity
Included with 
Get in-depth knowledge of a subject
Intermediate level
Recommended experience
3 months at 5 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
Get in-depth knowledge of a subject
Intermediate level
Recommended experience
3 months at 5 hours a week
Flexible schedule
Earn a career credential
Share your expertise with employers
What you'll learn
Build and evaluate machine learning models using Java libraries like Weka, Tribuo, and Deeplearning4j.
Deploy ML models in real-world Java applications using Spring Boot, Jenkins, and cloud-ready tools.
Apply advanced ML techniques including NLP, deep learning, and federated learning for enterprise use cases.
Overview
Skills you'll gain
Tools you'll learn
What’s included
Shareable certificate
Add to your LinkedIn profile
Taught in English
Recently updated!
June 2025
36 practice exercises
Advance your subject-matter expertise
- Learn in-demand skills from university and industry experts
- Master a subject or tool with hands-on projects
- Develop a deep understanding of key concepts
- Earn a career certificate from Board Infinity
Specialization - 3 course series
What you'll learn
Understand and apply core ML techniques using Java libraries
Apply supervised and unsupervised learning techniques such as regression, classification, and clustering.
Create end-to-end ML workflows in Java, including data preprocessing, model training, and performance evaluation.
Evaluate and debug Java-based ML models to improve performance, reliability, and readiness for real-world deployment scenarios.
Skills you'll gain
Category: Decision Tree Learning
Category: Debugging
Category: Regression Analysis
What you'll learn
Apply data preprocessing techniques using Java tools like Weka and Tribuo for machine learning tasks.
Build, train, and evaluate classification, regression, and deep learning models using DL4J, Tribuo, and DJL.
Implement NLP and scalable machine learning workflows using Apache OpenNLP, Spark MLlib, and Mahout.
Deploy machine learning models using standardized formats like PMML and ONNX, ensuring cross-platform interoperability and production readiness.
Skills you'll gain
Category: Java
Category: Java Programming
Category: Deep Learning
Category: Regression Analysis
Category: Natural Language Processing
Category: Data Processing
Category: Data Cleansing
Category: Application Deployment
Category: Applied Machine Learning
Category: Text Mining
Category: Data Transformation
Category: Machine Learning Algorithms
Category: Machine Learning
Category: Statistical Analysis
Category: Big Data
Category: Image Analysis
Category: Apache Spark
Category: Scalability
What you'll learn
Deploy ML models in Java applications using Spring Boot, REST APIs, and edge deployment tools.
Automate ML pipelines with MLOps tools like Jenkins and GitHub Actions.
Apply reinforcement learning, federated learning, and responsible AI practices in enterprise contexts.
Design and deploy a full-stack ML solution in Java through a capstone project, applying real-world data and production deployment strategies.
Skills you'll gain
Category: Spring Boot
Category: Machine Learning
Category: Continuous Monitoring
Category: Reinforcement Learning
Category: CI/CD
Category: Restful API
Category: Applied Machine Learning
Category: Deep Learning
Category: Jenkins
Category: Java
Category: Application Deployment
Category: Data Ethics
Category: MLOps (Machine Learning Operations)
Category: Spring Framework
Category: Artificial Intelligence
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructor
Offered by
Why people choose Coursera for their career
Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."
Open new doors with Coursera Plus
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Advance your career with an online degree
Earn a degree from world-class universities - 100% online
Join over 3,400 global companies that choose Coursera for Business
Upskill your employees to excel in the digital economy
Frequently asked questions
The specialization takes approximately 3 months to complete.
Learners should have a basic understanding of Java programming, object-oriented concepts, and foundational mathematics, including linear algebra and probability. Familiarity with data structures and algorithms is also helpful.
It is recommended to take the courses in sequence, as each builds on the previous one; however, learners with prior knowledge may start with any specific topic they wish to focus on.
More questions
Financial aid available,