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Lab manual and references for a four-hour, hands-on workshop that shows you how to build a working, private AI service running entirely on hardware you control, accessible securely across your team or engagement, with authentication built in.
The Artificial Intelligence Laboratory (AI LAB) Course Materials. This repository contains the source code and documentation for the practical exercises and experiments of an AI lab course. Developed primarily using Python within Jupyter Notebooks, the lab exercises focus on implementing fundamental AI algorithms.
Analysis of Algorithms Lab (5CS4-23, RTU Kota) — 10 experiments in Python with Excel input workbooks, complexity analysis, measured time-vs-n graphs, executed outputs and viva questions. Covers sorting, graph algorithms, dynamic programming, greedy methods and backtracking. Word and PDF manual plus source code.
A comprehensive lab manual for Raspberry Pi projects! 🤖 From Python fundamentals (loops, lists) to physical computing (LED matrix, PIR sensor, MQTT, web servers). Perfect for beginners and educators! 💡
A comprehensive, step-by-step academic lab manual for Cloud Computing and Security. Features hands-on experiments on virtualization, infrastructure provisioning (AWS EC2), serverless/PaaS development (Salesforce Apex), and cloud system simulation (CloudSim).