Python Tutorial: Complete Series From Basics To AI

Python + AI/ML Tutorial

This is the complete TechnoScripts Python series: 182 tutorials that take you from your very first line of code to building machine learning models and AI applications. Every post uses tested code with real output, and each part ends with a project you actually build. Start at post 001 or jump into the part that matches your level.

RAG System Design: The LLM Interview Whiteboard Round

RAG system design, short for Retrieval-Augmented Generation, is the GenAI whiteboard round where an interviewer says “design ChatPDF for an enterprise” and then watches how you think for forty-five minutes, not what you can draw. This post walks that round end to end: an eight-layer framework, two fully worked designs, the follow-up gauntlet on ACLs, freshness, and scale, and a mock transcript with the rubric, every number computed with real code. “They grade the numbers you defend, not the boxes ... Read More

Build an AI Portfolio That Gets Interviews: GitHub, Kaggle

Recruiters skim a stack of look-alike resumes; a link to shipped, evaluated work is what stops the scroll. An AI portfolio is that link, and the big AI employers say some version of the same thing on their careers pages: they hire on demonstrated, shipped work. If you followed this series, the projects already exist. This playbook turns that pile of repos into interviews. “Talk is cheap. Show me the code.” Linus Torvalds Last Updated: July 2026 | Tested on: ... Read More

Choosing an AI Tech Stack: 3 Real Case Studies

Teams pick the shiny tool first, bend the problem to fit it, and six months later a large language model is doing a job a hundred lines of scikit-learn would have nailed. Choosing an AI tech stack is where projects quietly go wrong before any model code exists. This post gives you a four-axis decision framework, then walks three real case studies to very different, defensible stacks. “The best stack is the boring one that clears your acceptance metric and ... Read More