LeetCode is dead.
Developers don't write code line-by-line anymore. They orchestrate AI agents working in parallel, review AI-generated code, and make architectural decisions.
That's the job now.
But most interview processes haven't caught up. They still test algorithm memorization instead of AI fluency, code review, and judgment.
We're building assessments for next-gen hiring that mirror how developers actually work. Here's how we think about it:
Libro gratis para aprender todo sobre Python desde cero!
→ Instalación
→ Configuración
→ Uso diario
→ Buenas prácticas
→ Creación de aplicaciones
→ Deploy
→ Recursos extra
Google acaba de presentar 3 herramientas gratis para ayudarte a estudiar utilizando Gemini ✨
1️⃣ Crea cuestionarios: Crea un cuestionarios para practicar Python.
2️⃣ Nuevo modo "Aprendizaje guiado": Quiero aprender programación desde cero.
3️⃣ Explicaciones mediante imágenes y vídeos: Explícame la arquitectura MVC.
¿Cuál es tu excusa para no aprender algo nuevo?
#MachineLearning Systems — Principles and Practices of Engineering Artificially Intelligent Systems: https://t.co/5bMmpZwAAB by @profvjreddi
[download 1660-page PDF]
“open-source textbook focuses on how to design and implement #AI systems effectively”
———
#ML#MLOps#DataScience
Desde esta semana ya tienes disponible el curso de Git y GitHub en mouredev pro. Junto a ejercicios, test, certificados, soporte y comunidad.
🟢 Cómo estudiar programación
🔵 Python desde cero
🌕 JavaScript desde cero
🟣 Git y GitHub desde cero
→ https://t.co/D5VFtU7RV3
Check out this book: https://t.co/QnqpD9CUFw — This is a fun way to learn Graph Algorithms and their many incredibly useful applications. "All the world is a graph", I always say!
➕➕
This author also wrote "Data Structures the Fun Way" — available at: https://t.co/PTzRnJEJuH
LLM Engineer's Handbook — Master the art of engineering Large Language Models #LLMs from concept to production: https://t.co/mVpoE6jfXG v/ @PacktPublishing
——
#DataScience#LLMOps#ML#GenAI#AI#GenerativeAI#MachineLearning
——
𝓦𝓱𝓪𝓽 𝔂𝓸𝓾 𝔀𝓲𝓵𝓵 𝓵𝓮𝓪𝓻𝓷:
🟢Implement robust data pipelines and manage LLM training cycles
🔵Create your own LLM and refine with the help of hands-on examples
🟢Get started with LLMOps by diving into core MLOps principles
🔵Perform supervised fine-tuning and LLM evaluation
🟢Deploy end-to-end LLM solutions using AWS and other tools
🔵Explore continuous training, monitoring, and logic automation
🟢Learn about RAG ingestion as well as inference and feature pipelines
#Python#MachineLearning By Example (4th Edition): https://t.co/3mO7oBt4gc
+
GitHub: https://t.co/XmXK8pz96h
——
#MachineLearning#ML#DataScience#DataScientist
——
518-page book! What you will learn:
🟣Machine learning best practices throughout data preparation and model development
🟣Build and improve image classifiers using convolutional neural networks (CNNs) and transfer learning
🟣Develop and fine-tune neural networks using TensorFlow and PyTorch
🟣Analyze sequence data and make predictions using recurrent neural networks (RNNs), transformers, and CLIP
🟣Build classifiers using support vector machines (SVMs) and boost performance with PCA
🟣Avoid overfitting using regularization, feature selection, and more
Si te gusta Python, en este artículo se comparan pros y contras de algunos de los frameworks de desarrollo web más potentes.
Reflex vs Django vs Flask vs Gradio vs Streamlit vs Dash vs FastAPI
→ https://t.co/PiQFOqWWEx
Data LLM is one of our top AI agents! It generates SQL queries and creates real-time dashboards from your data – no need for expensive, complex tools like Tableau.
Simplify your data insights instantly!
Hoy he tenido la suerte de dar mi primera charla en la PyCon de España 🤘
Momento para recordar que puedes aprender Python con mi curso gratis de 44 horas y 100 lecciones desde cero. Fundamentos, front, back...
→ https://t.co/VX7hjQaUB6