Inside the AI Runtime: PyTorch, C++, CUDA and Beyond
Understand the PyTorch runtime, from C++ and CUDA internals to TorchScript and AI-generated runtimes like VibeTensor, for high-performance AI.
Python
There is little to introduce to Python. It is well known by all developers.
Anything you want can be done with Python and this, together with its simplicity and simplicity, has made it one of the star programming languages today. It is a strongly typed object-oriented language in which it is especially important to maintain code readability.
It is the star language in data science, machine learning, deep learning, and everything related.
But you can still build web applications, or any other tool you can think of.
There are bookstores for everything!!!
In this section we solve some of the main problems that the Python developer often faces. In this way the way to become a ninja dev in python is assured.
Deep dive into Python Workout Second Edition
Discover Python Workout Second Edition: exercises, topics, and author insights to truly master practical Python step by step.
Layers of AI Observability for LLMs, Agents and Secure Operations
Discover the essential layers of AI observability to make LLMs and agents reliable, secure, cost‑efficient and compliant in real‑world production.
Scraping the Web with BeautifulSoup and Selenium
Learn when to use BeautifulSoup vs Selenium, how to combine them, and build ethical, robust web scrapers in Python for modern data projects.
Language Models From Scratch: From Tokens to Local LLMs
Understand large language models from tokens to transformers, quantization and local execution, explained in clear, practical English.
Selenium Tutorial For Beginners: From Zero To Stable Tests
Complete Selenium tutorial for beginners: WebDriver, waits, POM, Grid and best practices to build stable web test automation from scratch.
Microsoft Maia 200: the new in‑house AI accelerator redefining inference at scale
Maia 200 is Microsoft’s new in-house AI chip for fast, efficient inference in Azure, rivaling Trainium and TPU with over 10 PFLOPS of FP4 power.
Implementing Reinforcement Learning: From Theory to Real‑World Systems
Learn how reinforcement learning works, its algorithms, uses, risks and how to implement RL in real projects step by step.
AI model collapse in generative design and knowledge tools
Discover how AI model collapse affects generative design tools, why synthetic data is risky and what strategies can prevent long‑term degradation.