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Ai-Engineer

Ai-Engineer
Published 8/2026
Created by Cleuton Sampaio
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 76 Lectures ( 11h 57m ) | Size: 13.6 GB
Generate, review, and build production-ready software using advanced AI APIs, RAG, and Multi-Agent systems.


What you'll learn
⚡ Implement AI-enabled engineering workflows to accelerate system architecture, automate code generation, and optimize complex software delivery pipelines.
⚡ Integrate state-of-the-art LLM APIs into existing applications to add advanced semantic search, automated reasoning, and intelligent data processing.
⚡ Architect multi-agent engineering solutions that collaborate to solve real-world development problems, perform technical audits, and enforce best practices.
⚡ Master AI-driven engineering tools to streamline code analysis, identify architectural bottlenecks, and accelerate system refactoring tasks safely.
Requirements
❗ Experience in software development, solid understanding of programming logic, basic architecture concepts, and familiarity with APIs and command-line tools.
Description
This course contains the use of artificial intelligence.
Note: This version of the course uses Node.js / Typescript / React.
Transform your development workflow and master the next frontier of software engineering. This practical, hands-on course bridges the gap between traditional software development and AI-enabled engineering. Using a modern stack of Node.js, TypeScript, and React, you will move past basic prompting to build production-ready AI utilities, cognitive architectures, and autonomous workflows.
Throughout the course, you will engineer a complete portfolio of real-world applications from scratch
Foundations & API Mechanics: Master raw fetch requests, official SDKs, token counting, and prompt caching to maximize performance while minimizing API costs.
AI-Powered Programming Utilities: Build CLI tools and server-side APIs that perform autonomous code generation, automated code reviews, intelligent refactoring, and security scanning directly inside your CI/CD pipelines.
Advanced Tool Use & RAG: Implement function calling using JSON schemas to connect LLMs to web search, filesystems, and databases. Build a complete Retrieval-Augmented Generation system with semantic search using pgvector.
Agents & Multi-Agent Systems: Progress from basic chatbots to autonomous ReAct agents. Orchestrate a collaborative multi-agent development team featuring specialized Architect, Developer, QA, and Writer agents working in parallel to deliver full features autonomously.
Learn also about Spec-driven Development (SDD) and how to integrate it into your development workflow!
By the end, you will architect robust, cost-controlled AI systems, and master the AI-based workflow.
Who this course is for
⭐ Software developers, Software architects, Software Engineers, Data Engineers, QA professionals


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Tags : Ai, Engineer


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