Course Description

The AI Network certification course equips professionals with the essential knowledge and technical skills to master the intersection of artificial intelligence and advanced networking technologies. This program delves into core networking concepts such as Software-Defined Networking (SDN) and Network Function Virtualization (NFV) while exploring how AI revolutionizes network efficiency, scalability, and security. Participants will learn AI-powered automation techniques, orchestration strategies, and network optimization methods, enabling them to implement intelligent and efficient network operations. With hands-on projects and cutting-edge labs, learners gain practical experience to address real-world challenges. This certification prepares candidates to excel in AI-enhanced networking environments and secure leadership roles in the fast-evolving tech landscape.

Course Objectives

  • Master techniques to design and implement automated network operations powered by AI, reducing manual intervention and improving efficiency.​
  • Develop expertise in leveraging AI algorithms to detect, prevent, and mitigate cyber threats through real-time monitoring and predictive analytics.
  • Understand how to use AI tools for incident detection, response strategies, and forensic analysis to strengthen network defenses.
  • Learn to apply AI and machine learning for enhancing network performance, including faster data transfer speeds, reliability, and scalability.

Who Should Attend?

It’s designed for network engineers, cybersecurity professionals, and AI developers.

Course Agenda

  Module 1: Networking Foundations

  1.1 Basic Networking Concepts

  1.2 Networking Protocols and Standards

  1.3 Network Infrastructure and Design

  1.4 Introduction to Network Security

  Module 2: Advanced Networking Technologies

  2.1 Network Virtualization and Cloud Networking

  2.2 Emerging Network Architectures

  2.3 Advanced Routing and Switching

  2.4 Network Storage and Data Centers

  Module 3: AI in Networking

  3.1 Introduction to AI and Machine Learning

  3.2 AI-Driven Network Optimization

  3.3 AI for Network Security and Threat Detection

  3.4 AI-Enhanced Network Management

  Module 4: Network Automation and Orchestration

  4.1 Fundamentals of Network Automation

  4.2 AI-Driven Network Orchestration

  4.3 Policy-Driven Network Management

  4.4 Case Studies in Network Automation

  Module 5: AI-Enhanced Network Security

  5.1 Advanced Threat Detection with AI

  5.2 Secure Network Design and Architecture

  5.3 AI for Cybersecurity Intelligence

  5.4 Ethical Considerations in AI-Driven Security

  Module 6: Practical Labs and Hands-On Projects

  6.1 Network Simulation and Emulation

  6.2 AI-Driven Network Automation Projects

  6.3 AI for Network Security Projects

  6.4 Capstone Project (Using Google Colab and Azure cloud)

  Module 7: Emerging Trends and Future Directions

  7.1 Future of AI in Networking

  7.2 AI-Powered IoT Networks

  7.3 Blockchain and AI in Networking

  7.4 Continuous Learning and Career Development

  Optional Module: AI Agents for Network Management

  1. Understanding AI Agents

  2. Case Studies

  3. Hands-On Practice with AI Agents

Assessment Methodology

All courses conducted by EdTech will begin with a Pre-evaluation and end with a Post-evaluation. The instructor will evaluate the knowledge and skills of the participants according to the feedback given by participants. This will help to recognize the benefits and the level of knowledge gained by participants through the course.

Training Methodology

Facilitated by a highly qualified specialist, who has extensive knowledge and experience; this program will be conducted using extensively interactive methods, encouraging participants to share their own experiences and apply the program material to real-life work situations in order to stimulate group discussions and improve the efficiency of the subject coverage.

Percentages of the total course hour classification are:

  • ​40% Theoretical lectures, Concepts and approach
  • 20% Motivation to develop individual skill and Techniques
  • 20% Case Studies and Practical Exercises
  • 20% Topic General Discussions and interaction

Course Manual

Participants will be provided with comprehensive presentation material as reference manual. This presentation material is a compilation of core valuable information, references, presentation methods and inspiring reading which will be used as a part of the material guide.

Course Certificate

At the completion of the course, all participants who successfully accomplished the required contact hours will receive an EdTech Training Participation Certificate as a testimony to their commitment to professional development and further education.

Why Edtech ?

  • Industry Experienced; Internationally Qualified Trainers
  • Hands-on Practical Sessions & Assignments
  • Intensive Study materials
  • Flexible Schedules
  • Realistic training methodology
  • High-Quality Training in Affordable Course Fees
  • Achievement Certificate, as approved by the Ministry of Education (Abu Dhabi Center for Technical and Vocational Education Training - ACTVET), HABC, AWS, IAOSHE, SHRM, etc.