Optimize Java Data Performance for ML

Overview

As data analysis becomes a more essential part of software engineering, optimization techniques are an essential part of the analysis process. Java applications require careful consideration of memory management, due to how memory is managed in Java. To ensure that your applications run as efficiently as possible, you need to ensure that you select the right data management strategies for your projects. This comprehensive course equips developers with essential skills to build optimized data pipelines for Java applications. Through hands-on labs, you'll confidently analyze application memory profiles to implement data optimizations in your Java projects. If you're a software engineer, data analyst, or someone just interested in machine learning, this course is for you! Learn the essentials of data engineering and optimization for data projects. This course is designed for Java developers, data engineers, and ML practitioners who want to improve data handling, memory optimization, and performance in Java-based data pipelines. Learners should have basic Java programming skills, understand core data structures, and be comfortable building simple machine learning workflows in Java. By the end of this course, you’ll know how to optimize Java data structures, improve search and sort performance, and analyze memory usage to build faster, more efficient ML applications.

Syllabus

Structuring and Parsing Data

This module gives an overview of the different techniques for structuring and parsing data in Java applications. You'll explore how to choose data structures for different types of data, as well as how to optimize data loading through CSV loaders.

Storing and Searching Data

This module gives an overview of sorting and searching techniques for machine learning datasets. You'll explore how sorting and searching apply to projects, as well as how these techniques are typically applied.

Memory Management and Profiling

This module gives an overview of the memory management and profiling techniques commonly used with Java applications. The module also discusses how to use memory profiling to identify opportunities for memory optimization.