Introduction
簡介
In the rapidly evolving field of network management, automation, and programming tools are indispensable for their ability to streamline and simplify complex tasks. Tools like Python, Ansible, and Terraform have become essential for configuring network interfaces, managing infrastructure, and ensuring consistent deployments across diverse environments. These tools excel at predefined, rule-based tasks. They are useful for scenarios where network configurations follow clear, well-defined patterns and procedures.
在快速演變的網路管理領域，自動化與程式設計工具因能簡化並簡化複雜任務而不可或缺。Python、Ansible 與 Terraform 等工具已成為設定網路介面、管理基礎架構，並確保跨多元環境一致部署的必要工具。這些工具擅長處理預先定義、以規則為基礎的任務，適用於網路設定遵循明確、清楚定義之模式與流程的情境。
However, not all network challenges can be addressed with static, hardcoded solutions. This is where artificial intelligence (AI) and machine learning (ML) come into effect. These technologies are adept at recognizing patterns, predicting anomalies, and adapting to dynamic network environments.
然而，並非所有網路挑戰都能用靜態、寫死的解決方案處理。這正是人工智慧（AI）與機器學習（ML）發揮作用之處。這些技術擅長辨識模式、預測異常，並適應動態的網路環境。
Consider a company uses traditional firewalls and requires manual configuration of all policies. Network administrators must define each rule one by one, which is not only time-consuming, but also prone to human error. In addition, it's often difficult to think about all possible scenarios in cybersecurity.
假設一家公司使用傳統防火牆，需要手動設定所有政策。網路管理員必須逐一定義每條規則，這不僅耗時，也容易發生人為錯誤。此外，在網路安全領域往往很難考量到所有可能的情境。
You realize the following:
你會發現以下幾點：
- Static configuration is not always the preferred option.靜態設定並非總是首選方案。
- There is sometimes a need for pattern recognition, which would be difficult, or even impossible, to implement using classical programming approaches.有時需要模式識別能力，這種能力用傳統程式設計方式很難、甚至不可能實作。
- You might want to have a system for anomaly detection.你可能想要一套異常偵測系統。
- You would like to automate troubleshooting not only for security, but also in general network operations.你希望不只在安全性方面，也在一般網路維運方面自動化疑難排解。
Now, contrast this situation with a firewall that incorporates AI and ML capabilities. These advanced firewalls significantly reduce the burden of manual configuration and enhance security through intelligent, adaptive mechanisms. In addition, you can use specialized AI systems, capable of human-like dialogue, to address any warning or error message. These systems enable you to upload data and ask questions regarding that data, facilitating troubleshooting efforts.
現在，將這種情況與具備 AI 和 ML 能力的防火牆做對比。這類進階防火牆能大幅減少手動設定的負擔，並透過智慧、自我調整的機制提升安全性。此外，你還可以使用能進行類人對話的專用 AI 系統，來處理任何警告或錯誤訊息。這些系統讓你能上傳資料並針對該資料提問，有助於疑難排解工作。
In this course, you will learn the following:
在本課程中，你將學到以下內容：
- What is the difference between AI and ML?AI 與 ML 有何差異？
- What types of AI exist?AI 有哪些類型？
- What are neural networks and how they work?什麼是神經網路，它們如何運作？
- How the most popular algorithms used in generative AI work?生成式 AI 中最常用的演算法如何運作？
- What is retrieval augmented generation (RAG) and how it works?什麼是檢索增強生成（RAG），它如何運作？
- What is the role of AI and ML in network operations.AI 與 ML 在網路維運中扮演的角色。
