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Gen AI + Agentic AI with N8N + MCP with Claude Class 01 In Telugu 14th July 2026 08PM IST
🚀 *Gen AI + Agentic AI with N8N + MCP with Claude (Telugu)*
🗓️ *Date:* Contact +91 9059868766
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💡*Course Content:*
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This foundational class focuses on getting every student's local machine ready for development. It walks you through setting up a modern Python environment, exploring development tools, and addressing practical entry-level queries on Generative AI ecosystem dependencies.
Video Breakdown & Timestamps
[00:11] Class Agenda & Prerequisite Notes
The instructor reviews the previous demo session information, lays out the plan for the day, and introduces Anaconda, Python basics, and the development platforms to be used.
[02:25] Anaconda Distribution Setup Guide
A step-by-step walkthrough explaining why the Anaconda distribution is preferred over vanilla Python. The instructor demonstrates navigating the official site, handling installation configurations for Windows and Mac, and structuring download folders.
[10:18] Configuring Windows Environment Variables
Detailed instructions on adding the required installation paths into System Environment Variables for proper global terminal execution (applicable to Windows setups).
[14:44] Introduction to pip & Python IDEs
A comprehensive overview explaining why we require package managers like pip, exploring included development tools (Jupyter Notebook, Spyder), and comparing them to production tools like VS Code and PyCharm.
[19:26] Upgrading to Power Shell 7
A download and setup guide targeting Windows users to transition onto PowerShell 7 to gain better shell intelligence and script handling features.
[24:48] Launching Jupyter Notebook & Navigating the UI
Demonstration of launching the web-based IDE from targeted project paths using terminal commands, along with a troubleshooting workaround for manual fallback links.
[32:27] Essential Jupyter Notebook Shortcuts
A live demonstration showing how to efficiently control execution, create cells (Escape + A/B), remove sections (D + D), and convert blocks to Markdown documentation formats (Escape + M/Y).
[43:23] Q&A: Programming Ecosystem for Generative AI
The session transitions into an open discussion addressing student queries, including:
Why Python is dominant over Java, Go, and TypeScript in AI engineering.
Exploring model hosting hubs (Hugging Face) and localized model testers (Ollama, LM Studio).
The fundamental difference between model selection benchmarks and Prompt Engineering rules.
How non-programmers can transition smoothly into building complete AI agent applications.
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