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Intermediate
14 Semanas est.
Full-Stack AI & LLM Application Engineer
Master the end-to-end stack required to build, evaluate, and deploy production-ready AI applications using Python, LangChain, OpenAI/NVIDIA APIs, Next.js, and Vector Databases.
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🪜 Etapas de aprendizaje secuencial (4 fases):
#1
Python & Backend Foundations
Core Python programming, OOP, asynchronous programming, and REST APIs with FastAPI.
🎯 🎯 Habilidades dominadas en la etapa:
Python 3.12, Asynchronous I/O, REST APIs, Git, Virtual Environments
Cursos gratis recomendados para esta etapa:
freeCodeCamp
100% GRATIS
Scientific Computing with Python Certification
⭐ 4.9
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Harvard University
100% GRATIS
CS50: Introduction to Computer Science
⭐ 4.9
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#2
Prompt Engineering & LLM Orchestration
Understanding Large Language Models, embeddings, prompt chains, and RAG architectures.
🎯 🎯 Habilidades dominadas en la etapa:
Prompt Engineering, RAG, LangChain, Vector Embeddings, ChromaDB
Cursos gratis recomendados para esta etapa:
Udemy
100% GRATIS
Internal Audit: Risk, Controls and the Audit Process [EN]
⭐ 5.0
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Stanford University & DeepLearning.AI
100% GRATIS
Supervised Machine Learning: Regression and Classification
⭐ 4.9
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#3
Frontend Integration & UI UX
Build streaming AI interfaces, chat UIs, and real-time dashboard experiences.
🎯 🎯 Habilidades dominadas en la etapa:
JavaScript, React, Tailwind CSS, WebSockets, Streaming UI
Cursos gratis recomendados para esta etapa:
Harvard University
100% GRATIS
CS50's Web Programming with Python and JavaScript
⭐ 4.8
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#4
Cloud Deployment & Production Scaling
Deploying containerized AI microservices on Docker and cloud platforms with monitoring.
🎯 🎯 Habilidades dominadas en la etapa:
Docker, Linux, Cloud Deployments, Model Latency Optimization
Cursos gratis recomendados para esta etapa:
The Linux Foundation
100% GRATIS
Introduction to Kubernetes (LFS158x)
⭐ 4.8
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Coursera Partner
100% GRATIS
Use SurveyMonkey to Create a Survey and Analyze Results
⭐ 4.8
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