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Practical Java, Spring Boot, Microservices and AI Tutorials

Build stronger software-development skills through clear explanations, practical examples and structured learning paths.

Explore tutorials Interview preparation
Clear explanationsConcepts broken into useful steps
Practical examplesImplementation-focused guidance
Structured pathsProgress from foundations onward
All experience levelsFor students and developers

Choose Your Learning Path

Follow focused topics from essential concepts to practical implementation.

Java

Core Java, collections, concurrency, memory management and modern language features.

Spring & Spring Boot

Spring fundamentals, dependency injection, data access and application development.

Microservices

Service architecture, communication, resiliency, observability and distributed systems.

Docker & Kubernetes

Containers, networking, storage, orchestration and deployment fundamentals.

Generative AI

Language models, prompting, evaluation, data privacy and secure AI development.

Interview Preparation

Java, Spring, microservices and system-design concepts for technical interviews.

Start with these in-depth collections covering software design, architecture and secure AI.

Java guide

Java Design Patterns

Explore creational, structural and behavioral patterns with practical Java-focused explanations.

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Architecture guide

Microservices Design Principles

Learn how autonomy, ownership, observability, resiliency and automation shape reliable systems.

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AI security guide

Generative AI: Data Privacy and Safe Use

Understand privacy risks, adversarial attacks, data poisoning and responsible AI governance.

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Latest Tutorials

Recently published and updated resources from CodingKnownSense.

AI privacy

Membership Inference Attacks

Learn how attackers determine whether a record was used to train a model and how teams can reduce the risk.

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AI security

Data Poisoning Attacks

Understand how manipulated training data changes model behavior and the controls that protect ML pipelines.

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AI security

Adversarial Attacks on AI

Explore deceptive inputs, common attack categories and practical defensive measures for AI systems.

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Governance

LLMOps Governance and Compliance

Build clear ownership, policies and automated checks around the development and deployment of language models.

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OWASP

OWASP Top 10 Risks for LLMs

Review important security risks for connected LLM applications with examples and mitigation guidance.

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Generative AI

Advanced Applications of LLMs

Move beyond isolated prompts and explore agents, APIs, memory and tool-connected AI systems.

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Why CodingKnownSense?

A focused technical library for understanding concepts and applying them with confidence.

Clear explanations

Complex topics are divided into focused, manageable sections.

Practical focus

Examples connect definitions with implementation decisions.

Structured learning

Related guides help readers move from foundations to advanced topics.

Developer-oriented

Content serves students, working developers and interview candidates.

About the publication

Practical knowledge for modern developers

CodingKnownSense is an independent technical-learning publication covering Java, Spring Boot, microservices, Docker, Kubernetes and generative AI.

Its purpose is to organize complex development topics into clear explanations, implementation-focused guides and structured resources for students, working developers and technical interview candidates.

About CodingKnownSense
Our publishing goal is to make technical concepts practical, understandable and useful in real development work.

Ready to strengthen your development skills?

Choose a learning path, explore practical tutorials and build a stronger understanding of modern software development.

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