Apply SOLID Design to Optimize Java ML

本课程是 Level Up: Java-Powered Machine Learning 专项课程的一部分

位教师：Scott Cosentino

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4个模块

深入了解一个主题并学习基础知识。

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5 小时完成

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自行安排学习进度

4个模块

深入了解一个主题并学习基础知识。

高级设置等级

推荐体验

5 小时完成

灵活的计划

自行安排学习进度

您将学到什么

Apply the Single Responsibility Principle (SRP) and Open/Closed Principle (OCP) to create modular and extensible components.
Implement the Liskov Substitution Principle (LSP) and the Dependency Inversion Principle (DIP) to build flexible and decoupled components.
Utilize Maven and Gradle to manage dependencies and structure a Java ML project.
Evaluate design trade-offs when applying SOLID principles to a Java ML project.

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该课程共有4个模块

"Tired of ""God Classes"" and spaghetti code in your Java ML projects? This course, ""Enhance Java ML Design with SOLID Principles,"" is for senior developers and architects ready to build resilient software. The secret to reliable systems is accepting that requirements always evolve. Master the S.O.L.I.D. principles to write code that embraces future changes with minimal impact.

This course is designed for senior Java developers and architects with at least 6 months of hands-on experience in Java programming and basic knowledge of machine learning. If you're ready to tackle "God Classes" and spaghetti code, and want to optimize your Java ML projects with SOLID principles for scalability, maintainability, and flexibility, this course is for you. To get the most out of this course, learners should have at least 6 months of hands-on experience with Java programming, including a solid understanding of object-oriented programming (OOP) concepts such as classes, interfaces, and abstract classes. Additionally, a basic knowledge of machine learning (ML) concepts is essential to fully grasp how to apply SOLID principles to Java ML projects. By the end of this course, you’ve unlocked the power of SOLID principles to create flexible, scalable, and maintainable Java ML systems. You now have the tools to refactor messy code, design modular components, and evaluate trade-offs between performance and design. With your newfound expertise in SOLID, Maven, Gradle, and best practices, you're ready to build production-ready machine learning applications that can evolve with ease. Keep applying these principles, and your code will become more reliable and adaptable with every project. Best of luck as you continue to level up your skills in Java and machine learning!

In this module, learners will start with a messy "ModelHandler" class that violates multiple SOLID principles. Learners will learn to identify code smells, understand the business impact of poor design, and systematically refactor using SRP and OCP. By the end, learners will have transformed a monolithic class into a clean, modular system that's ready for future changes.

涵盖的内容

4个视频2篇阅读材料1次同伴评审

4个视频总计20分钟

Welcome to Enhancing Java ML Design with SOLID Principles 3分钟
Dissecting the "God Class" Problem 5分钟
Single Responsibility Principle in Action 5分钟
Open/Closed Principle: Planning for Change 7分钟

2篇阅读材料总计10分钟

Welcome to the Course: Course Overview 5分钟
The Cost of Bad Design 5分钟

1次同伴评审总计30分钟

Hands-On-Learning: Refactor a Monolithic Class Using Single Responsibility Principle 30分钟

This lesson focuses on creating truly flexible ML systems. You'll learn how LSP ensures your abstractions work correctly with any implementation, while DIP helps you build systems that depend on abstractions rather than concrete implementations. We'll show how to swap out different ML models and data sources without breaking your application.

涵盖的内容

3个视频1篇阅读材料1次同伴评审

In this lesson, you'll learn to design clean, focused interfaces that don't force clients to depend on methods they don't use. We'll also dive into practical project management with Maven and Gradle, showing how proper build tool configuration supports clean architecture and manages the complex dependency trees common in ML projects.

涵盖的内容

3个视频1篇阅读材料1次同伴评审

3个视频总计17分钟

Interface Segregation Principle: Right-Sized Contracts 6分钟
Maven for ML Projects: Dependency Harmony 6分钟
Gradle Alternative: Modern Build Automation 6分钟

1篇阅读材料总计5分钟

Build Tool Best Practices for ML 5分钟

1次同伴评审总计20分钟

Hands-On-Learning: Leveraging Maven and Gradle to Install Dependencies for an ML Project 20分钟

This final lesson brings everything together by examining real-world scenarios where strict adherence to SOLID principles might conflict with practical concerns like performance, simplicity, or time constraints. You'll develop a framework for making pragmatic design decisions and learn when to prioritize certain principles over others.

涵盖的内容

5个视频1篇阅读材料1个作业2次同伴评审

5个视频总计25分钟

When SOLID Meets Reality: Performance vs Principles 9分钟
The Pragmatic Approach: Design Decision Framework 5分钟
Basic Patterns: Factory Pattern 4分钟
Basic Patterns: Strategy Pattern 4分钟
Congratulations and Your SOLID Foundation 2分钟

1篇阅读材料总计5分钟

Clean Architecture in Practice 5分钟

1个作业总计20分钟

Apply SOLID Design to Optimize Java ML 20分钟

2次同伴评审总计80分钟

Hands-On-Learning: Balancing SOLID Design and Performance in High-Throughput ML Systems 20分钟
Project: Adaptive Combat Strategist (ML Edition) 60分钟

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位教师

Scott Cosentino

Coursera

10 门课程 1,116 名学生

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