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AI Fundamentals for Network Engineers by Arash Deljoo
Rating: 4.8 out of 5(26 ratings)
199 students
Created byArash Deljoo
Last updated 10/2025
English

What you'll learn

  • AI Unleashed for Network Engineers: Build Smarter, Faster, Stronger Networks
  • Decoding the Network Brain: How AI Thinks, Learns, and Optimizes Connectivity
  • Automate the Future: AI Skills Every Network Engineer Must Know
  • Smarter Networks, Smarter Engineers: Master AI Fundamentals in Networking
  • The AI Advantage: Transform Your Network Engineering Career

Course content

2 sections • 20 lectures • 2h 33m total length

  • Understanding AI and Machine Learning6:35

    1- Artificial Intelligence (AI)

    2- Machine Learning (ML)

    3- The relationship between AI and ML

    4- Contrasting Traditional Programming with Machine Learning

    5- Key ML processes: Learning, Reasoning, and Self-Correction

    6- Types of Data used in ML (Images, Text, Numerical)

    7- Functions of ML systems: Descriptive, Predictive, and Prescriptive

  • Understanding AI and Machine Learning Quiz
  • The Three Ways AI Learns6:08

    1- Supervised Learning

    2- Unlabeled Data

    3- Reinforcement Learning

    4- Labeled Data

    5- Anomaly Detection

    6- Trial-and-Error Learning

    7- Pattern Recognition

  • The Three Ways AI Learns Quiz
  • How AI and ML are Revolutionizing Network Operations6:54

    1-Predictive Maintenance

    2-Anomaly Detection and Security

    3-Traffic Analysis and Management

    4-Automated Configuration and Management

    5-Root Cause Analysis

    6-Proactive Management

    7-Quality of Service (QoS)

  • How AI and ML are Revolutionizing Network Operations Quiz
  • Types of Artificial Intelligence8:08

    1-Predictive AI

    2-Generative AI

    3-Generative Pre-Trained Transformer (GPT)

    4-Publicly Available GPT Models

  • Types of Artificial Intelligence Quiz
  • Prompt Engineering for Network Engineers4:44

    1-Importance of Question Phrasing

    2-How LLMs Interpret Language Relationships

    3-Role of Vocabulary and Clarity in AI Prompts

    4-Example: Network Engineering and Specific Prompts

  • Prompt Engineering for Network Engineers Quiz
  • Reducing Hallucinations for Accurate Answers9:26

    1- Hallucination in LLMs

    2- Why retraining is not always enough

    3- Retrieval-Augmented Generation (RAG) overview

    4- RAG pipeline: indexing → retrieval → generation

    5- Using RAG with ChatGPT (uploading docs)

    6- RAG limitations and caveats

    7- Best practices to reduce inaccuracies

  • Reducing Hallucinations for Accurate Answers Quiz
  • Simplifying Network Automation5:21

    1- The Challenge of Network Automation

    2- How GPT Helps You Write Code Without Knowing the Language

    3- Ansible and YAML Overview

    4- Using GPT to Generate Automation Code

    5- Beyond YAML , Generating Python Code

  • Simplifying Network Automation Quiz
  • Understanding Network Errors with AI5:13

    1- Why Network Error Messages Are Confusing

    2- How GPT Helps You Translate and Solve Errors

    3- Why GPT Is Useful for Engineers

    4- Real-World Scenario Example

    5- GPT as a Learning Partner

  • Understanding Network Errors with AI Quiz
  • LLMs’ Limits and Cisco’s Smart AI Solutions3:57

    1-Large Language Models (LLMs)

    2-Limitations of LLMs

    3-Cisco AIOps Solutions

    4-Predictive Maintenance

    5-Anomaly Detection

    6-Dynamic Traffic Management

    7-Integration of LLMs with Cisco AIOps

  • LLMs’ Limits and Cisco’s Smart AI Solutions Quiz
  • Smarter Networks with Cisco AIOps AI and ML in Action6:56

    1-Cisco AIOps Overview

    2-Cisco Catalyst Center

    3-Cisco Nexus Dashboard & Insights

    4-Cisco Meraki

    5-Cisco AppDynamics

    6-Cisco ThousandEyes

    7-Cisco Secure Network Analytics

  • Smarter Networks with Cisco AIOps AI and ML in Action Quiz
  • Security considerations when using GPT6:51

    1-Public vs. Private GPT Instances

    2-Data Sensitivity: What to Share and What Not to Share

    3-Prompt Injection Attacks

    4-Real-World Example: The Code Injection

    5-Strengthening Security with Audits and Access Controls

  • Security considerations when using GPT Quiz

Requirements

  • Some prior experience in IT, computer science, or systems administration is helpful but not mandatory. Anyone with a technical mindset and curiosity about AI’s impact on networking can succeed.

Description

Welcome to AI Fundamentals for Network Engineers, a comprehensive course designed to bridge the gap between artificial intelligence and modern network operations. This course introduces network engineers to the core concepts of AI and machine learning, exploring how these technologies are revolutionizing network management, automation, and security. You’ll start by understanding AI fundamentals, the different ways AI learns, and the types of AI that are shaping the future of networking. Practical topics such as prompt engineering, reducing hallucinations for accurate answers, and leveraging AI to simplify network automation are also covered. Additionally, students will gain insights into understanding network errors with AI, the limits of large language models, and Cisco’s innovative Smart AI solutions for smarter, more secure networks.

The course also provides a deep dive into Cisco AIOps, detailing its vision, tools, and how AI-driven operations are transforming traditional network management. Key topics include agentic operations, full-stack observability, the core pillars of AIOps, and a comparison of Cisco Observability Platform versus standalone AIOps solutions.

Please note that this course is currently under construction, and more content and advanced topics will be added over time. As the course evolves, learners can expect to gain an even deeper understanding of how AI can optimize, automate, and secure networks, ensuring they stay ahead in the rapidly evolving world of network engineering. Whether you are a beginner or an experienced engineer, this course provides the foundational knowledge and practical insights needed to harness AI effectively in your network operations.

Who this course is for:

  • Network Engineers and Administrators
  • IT Professionals and System Engineers
  • Students and Recent Graduates in Networking or Computer Science
  • Network Operations Center (NOC) and Security Operations Center (SOC) Teams
  • Tech Enthusiasts Exploring AI in Networking

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