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Learning library

Build foundations by topic

These hubs organize TechEazy's preserved guides without moving their bookmarked URLs. Start with the foundation you need, then follow the connected program pathway when it fits your goal.

AWS and Cloud Engineering

Practical guides to load balancing, scaling, deployment, and resilient AWS foundations.

Java and Spring Engineering

Build a sound Java foundation, then apply Spring Boot, dependency injection, MVC, and REST.

Git and GitHub Collaboration

Learn repository, branch, pull-request, protection, and delivery workflows used by engineering teams.

Technology Career Foundations

Durable guidance for choosing core skills, presenting your work, and building credible career evidence.

5 free courses · no sign-in

Prefer a guided path? Take a free course

Every session is public: open a course and start. Nothing to sign up for, nothing to pay.

FreeBeginner

Hands-on Cloud for Freshers

8 sessions · self-paced · read online

Eight hands-on sessions on AWS for freshers: a safe account, permissions, storage, servers, networks, a database and serverless code, ending in a small app you deploy and then tear down.

FreeBeginner

Getting Started with AI

8 sessions · self-paced · read online

Eight sessions on how language models really behave: tokens and sampling, cost and latency, prompts and context, structured output, choosing a provider, and using AI responsibly.

FreeIntermediate

Build and Evaluate RAG Applications

8 sessions · self-paced · read online

Eight sessions on retrieval-augmented generation: embeddings and vector search, grounded answers with citations, why retrieval fails, evaluation suites and catching hallucinations.

FreeIntermediate

Building AI Agents

11 sessions · self-paced · read online

Eleven sessions on agents that take real actions: tool calling, the Model Context Protocol, the agent loop, memory, access control, human approval and guardrails, ending in a capstone feature.

FreeIntermediate

Taking AI to Production

9 sessions · self-paced · read online

Nine sessions on running AI systems for real: where models run, reference architectures, scaling, cost, observability and audit, ending in a design you defend with decision records.

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