Udemy

Python Learning for Network Engineers Automation Masterclass

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  • 21,179 名學生
  • 更新於 3/2026
4.4
(538 個評分)
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課程資料

報名日期
全年招生
課程級別
學習模式
教學語言
英語
授課導師
Shibi Dev
評分
4.4
(538 個評分)
3次瀏覽

課程簡介

Python Learning for Network Engineers Automation Masterclass

100% Hands-on Python training session with real time Network Automation usecases(SSH, NETCONF, RESTCONF& API examples)

Learn Network Automation skills from scratch to an advanced level.

For attending this course you don't need any prior coding experience.


You will be learning all the required Python concepts in a practical way with Networking Examples

2026 Updated AI Topics:

  1. Model Context Protocol (MCP) -

    1. UV Environment Setup

    2. Add Additional Libraries to MCP

    3. Build Device Automation MCP Server

    4. Build simple MCP Client

    5. Playwright MCP

  2. Agentic AI Workflows -

    1. Async & Await Deep dive

    2. OpenAI Tracing

    3. Pydantic Structured Data

    4. Gemini 3 Thinking Levels

    5. Gemini3 Get Structured Output using Pydantic

    6. Build Multi Agent Config Gatekeeper Agentic AI Workflow


This course is designed for Network Engineers with less or no coding experience.

Throughout the session, we will be using Linux OS (preferably Ubuntu) for running Python scripts.

This course is updated with steps to setup Cisco Modeling Lab (CML) Free Tier for automation Practices

The IDE is VS Code and Cisco devices will be used for demonstrating most of the device interactions. (vIOS, IOS-XE, NXOS etc)


  • The course will be starting with SSH fundamentals

  • Initially, Course will take you through Paramiko, Netmiko, NAPALM and Nornir Libraries' fundamentals

  • CIsco IOS, NXOS, Cisco DNAC Automation Examples

  • Paramiko invoke_shell and exec_command methods

  • Pydantic for structured data

  • Python UV Environment Setup

  • Setup Model Context Protocol (MCP) Server for Network Automation

  • Async & Await Deep Dive

  • Gemini 3 Multi Agent Framework

  • OpenAI Tracing

  • Methods supported in Netmiko for device interactions

  • How to do Configuration parsing using Regular Expressions over SSH

  • How to enable logging in the script with a log file or event email triggers

  • How to schedule the Script execution without keeping the terminal opened

  • How to do IP address and subnet validations using Python

  • How to do multithreading for parallel execution on multiple devices

  • Read and write contents to a text file, JSON, YAML, and XML

  • Manage device inventories or config details in CSV files

  • Read the configuration data from CSV, YAML, JSON, or text files

  • How to use textfsm template

  • How to use Jinja2 templates for creating multiline configuration templates with loops or conditions

  • How to use NAPALM for multivendor support

  • How to use getters in NAPALM

  • How to use config merge, config compare, config replace and config rollback in NAPALMcreate

  • What is Nornir Framework

  • How to create an inventory file in Nornir

  • How to create tasks in Nornir

  • What are plugins in Nornir

  • NETCONF/YANG Data models with real-time examples

  • Netconf Automation using Python Ncclient

  • RESTCONF API Automation using Requests

  • Cisco Nexus Automation with NX-API (CLI, JSON-RPC, error handling, parsing outputs)

  • Cisco PyATS framework for testing, parsing, config compare, and automation workflows

  • MCP (Model Context Protocol) with Python: build AI-powered automation, create smart apps, automate Cisco configs, browser automation with Playwright, and integrate GenAI into network workflows

  • Generative AI with Python: Build basic LangChain apps, ChatPromptTemplates, Language Translator apps using Groq API & OpenAI, and integrate GenAI into network automation use cases

  • Raspberry Pi Micropython Network Monitoring and Automation examples

Course Update log (Latest Topics):


  1. March 2026 - Added Agentic AI Videos

  2. January 2026 - Added Agentic AI Usecases

  3. Sept 2025: MCP (Model Context Protocol) + GenAI Integration with Python

  4. 2023–2024: Generative AI Projects (LangChain, Groq API, OpenAI API, Streamlit Apps)

  5. June 2023: Raspberry Pi Micro Python

  6. May 2023: Command Line Arguments using Argparse

  7. April 2023: VMWare ESXi CLI automation using Python

Python Fundamentals Covered:

  • Strings and String Methods

  • Bytes and Unicode

  • Exception handling

  • stdin, stdout, stderr in Python

  • File Operations

  • Config HTML Comparison using Python

  • Regex Fundamentals

  • For loop

  • While loop

  • if, else, elif

  • Functions and Modules

  • Object Oriented Programming: Classes Basics

  • Multithreading

  • lists, dictionaries, and its methods

  • sets, tuples

  • Pycharm debug Example

  • Mutable vs Immutable

  • datetime

  • schedule

  • Logging

  • Enumerate

  • Tabulate

  • Itemgettes

  • List comprehension

  • copy and deep copy

  • subprocess

  • JSON

  • XML

  • YAML

  • Mocropython for beginners

  • MCP Libraries (mcp, mcp_use, Playwright MCP, etc.)

  • Generative AI Libraries (LangChain, OpenAI, Groq API, Streamlit integration)


課程章節

  • 36 個章節
  • 249 堂課
  • 第 1 章 Introduction & Course Walkthrough
  • 第 2 章 Lab Setup V2(Latest) - Cisco Modeling Lab(CML ) Free Tier -(2026 January)
  • 第 3 章 Lab Setup V1 - Using VisualStudio Code : Remote Development
  • 第 4 章 Lab Setup V0 - Optional (Old Approach)-Using PyCharm, VirtualBox and Ubuntu GNS3
  • 第 5 章 Paramiko
  • 第 6 章 File Operations
  • 第 7 章 String Methods
  • 第 8 章 Config Compare
  • 第 9 章 RegEx Fundamentals
  • 第 10 章 RegEx show command Parsing Examples
  • 第 11 章 IP Address Module
  • 第 12 章 Python Functions
  • 第 13 章 Python Modules
  • 第 14 章 Python Classes and Objects : Basics
  • 第 15 章 Python : Data Types
  • 第 16 章 PyCharm Debug
  • 第 17 章 Loops and Conditionals
  • 第 18 章 Python Multithreading
  • 第 19 章 CSV Files
  • 第 20 章 Logging
  • 第 21 章 Userful Python Concenpts
  • 第 22 章 NETMIKO
  • 第 23 章 Data Serialization & Templates
  • 第 24 章 MCP(Model Context Protocol) - Examples - GenAI Tutorial
  • 第 25 章 Agentic AI Example for Network Automation - Build Config Gatekeeper
  • 第 26 章 NAPALM Python Library
  • 第 27 章 Nornir
  • 第 28 章 NETCONF
  • 第 29 章 YANG Suite
  • 第 30 章 RESTCONF
  • 第 31 章 Cisco DNAC Automation
  • 第 32 章 Cisco Nexus API (NXAPI -CLI)
  • 第 33 章 PyATS Framework
  • 第 34 章 Miscellaneous Automation Topics
  • 第 35 章 Raspberry Pi Micropython Automation
  • 第 36 章 Getting Started with GenerativeAI - Create a simple Language Translator App

課程內容

  • Master Python Network Automation concepts from scratch. No prior coding experience is needed, Learn about Paramiko, Netmiko, NAPALM, Nornir, NETCONF, RESTCONF, YANG Models, Ncclient,API Requests, IPAddress libraries in python for Network automation, Agentic AI Network Automation Example - Config Gatekeeper using Gemini 3, Acclerate your career to become the future-ready Network Automation Engineer, UV Python Environment Setup, Model Context Protocol (MCP) - Network Automation Example, Async & Await - Agentic AI Tutorials, Learn to automate SSH, NETCONF, RESTCONF and API device interactions using Python, Learn to automate day to day Network Device configuration tasks and solve realtime Networking Automation usecases in more practical way, Learn to setup Ubuntu OS and PyCharm for your Network Automation Journey, Learn to do the Network Sniffing anf Packet capture using Python, Learn to prase device configuration using RegularExpression, Learn about SSH Keybased Authentication, Learn all the Python3 core concepts from Network context, Learn to use Jinja2 templates and textfsm in your scripts, Learn to use functions and Classes in Python for Network Automation, Learn about scheduling the task execution and logging the script execution results, Create and use CSV, YAML, JSON, XML files in your Python Automation scripts and device configurations


評價

  • A
    Abraham Atenya
    3.0

    We started off with VMWare Workstation and already set it up. Why we now shit again to VMWare Player yet GNS3 can still run on VMWare workstation begs questions. Now, can we have a standard way or do we have to run all these softwares on our PCs, remember they consume a lot of RAM

  • P
    Polumuri Lova Kumar
    5.0

    good

  • S
    Sara shareef
    1.0

    not good explanation.

  • D
    Deepak Sharma
    3.0

    Great content

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