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    • AI+ Network Practitioner™

    This certification validates professional knowledge and competency in the combination of artificial intelligence and current networking technologies. The exam assesses understanding of fundamental networking concepts, newer technologies such as SDN and NFV, and how AI can enhance network efficiency. Key focus areas include AI-powered network automation, orchestration, and security upgrades. The exam includes scenario-based questions covering emerging developments in AI-enhanced networking, validating candidate readiness for leadership roles in this rapidly evolving sector.
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    AI+ Network Practitioner™
    Price: USD $495.00

    At a Glance: Course + Exam Overview

    Category AI Security
    AI Technical
    Program Name AI+ Network Practitioner™
    Prerequisites
      • Networking Fundamentals: Understand basic networking concepts, routing and switching, IP addressing, VLANs, network security, and common enterprise network architectures.
      • AI and Machine Learning Fundamentals: Understand basic AI and ML concepts, supervised and unsupervised learning, anomaly detection, and how AI can support network operations.
      • Python and Automation Awareness: Have basic familiarity with Python, scripting, APIs, and automation concepts used in programmable network environments.
      • Cloud and Modern Infrastructure Awareness: Recognize cloud networking, virtualization, data centers, wireless networks, edge computing, IoT, and hybrid connectivity concepts.
      • Network Operations and Security Awareness: Understand monitoring, telemetry, troubleshooting, access control, security operations, and the need for human oversight when AI is used in network decisions.
    Exam Format 90 minutes

    What You'll Learn

    Certification Modules

    Module 1: Enterprise Networking Foundations & AI Workload Impact

    1. 1.1 Basic Networking Concepts
    2. 1.2 Network Infrastructure and Design
    3. 1.3 Introduction to Network Security
    4. 1.4 AI Workload Networking Overview

    Module 2: Advanced Routing, Switching, and Data Center/AI Fabric Networking

    1. 2.1 Advanced Routing and Switching
    2. 2.2 Data Center and AI Infrastructure Networking
    3. 2.3 High-Performance AI Fabric Considerations
    4. 2.4 Quality of Service (QoS) for Application and AI Workloads

    Module 3: Cloud Networking, SASE, and Hybrid Connectivity

    1. 3.1 Network Virtualization and Cloud Networking Models
    2. 3.2 SD-WAN and Hybrid Multi-Cloud Connectivity
    3. 3.3 SASE and SSE with AI

    Module 4: Wi-Fi 7, Edge AI & IoT Networking

    1. 4.1 Wi-Fi 7 and AI-Driven RF Optimization
    2. 4.2 Edge Computing, Fog Networking and IoT Models
    3. 4.3 Edge AI and Small Language Models
    4. 4.4 Wi-Fi 7 + Edge AI Use Cases and Architecture

    Module 5: AI & Machine Learning Foundations for Network Engineers

    1. 5.1 AI and Machine Learning Fundamentals
    2. 5.2 AI-Driven Network Optimization
    3. 5.3 Operational Limits of AI Recommendations
    4. 5.4 Predictive Network Maintenance

    Module 6: Generative AI, RAG, and Prompt Engineering for Operations

    1. 6.1 Generative AI and LLM Concepts for Network Operations
    2. 6.2 RAG (Retrieval-Augmented Generation) for Network Knowledge
    3. 6.3 Prompt Engineering for Network Engineers

    Module 7: Network Automation, IaC, and Agentic AI Workflows

    1. 7.1 Fundamentals of Network Automation & Infrastructure as Code (IaC)
    2. 7.2 Network APIs and Programmability
    3. 7.3 Agentic AI, Function Calling, and MCP
    4. 7.4 ChatOps and Operational Workflows
    5. 7.5 Use-Cases and Case Studies

    Module 8: AI-Enhanced Network Security and Zero Trust

    1. 8.1 AI-Enhanced Threat Detection
    2. 8.2 Secure Network Design and Zero Trust
    3. 8.3 SIEM, SOC, and AI-Assisted Security Operations
    4. 8.4 Adversarial AI and AI Security Risks
    5. 8.5 Use-Cases and Case Studies

    Module 9: Modern Observability: eBPF, OpenTelemetry, and AIOps

    1. 9.1 Modern Observability Foundations (Metrics, Logs, and Traces)
    2. 9.2 eBPF for Deep Network Visibility
    3. 9.3 OpenTelemetry and Streaming Telemetry Standards
    4. 9.4 AIOps: Alert Correlation, Noise Reduction, and Root Cause Support
    5. 9.5 Use-Cases and Case Studies

    Module 10: AI Governance, Responsible AI, and Sustainable Networking

    1. 10.1 AI Governance and Responsible Network Operations
    2. 10.2 Privacy, Data Handling, and Bias in Network AI
    3. 10.3 Sustainable/Green Networking with AI
    4. 10.4 Future Network Operations
    5. 10.5 Use-Cases and Case Studies

    Module 11: Capstone Project - End-to-End AI Network Operations

    1. 11.1 Capstone Objective
    2. 11.2 Capstone Scenario

    Optional Module: Optional Module: AI Agents For Network

    1. 1.1 What Are AI Agents
    2. 1.2 Applications and Trends of AI Agents in Network Intelligence
    3. 1.3 How Does an AI Agent Work
    4. 1.4 Characteristics of AI Agents
    5. 1.5 Types of AI Agents

    Finish the course and get certified

    Certificate 1

    Industry Opportunities

    • Network Support Specialist
      Network Support Specialist
      Provide technical support by troubleshooting network issues and ensuring reliable connectivity across enterprise environments.
    • Junior Network Engineer
      Junior Network Engineer
      Assist in designing, configuring, and maintaining network infrastructure to support secure and efficient operations.
    • Network Operations Center (NOC) Analyst
      Network Operations Center (NOC) Analyst
      Monitor network performance, detect outages, and respond to incidents to ensure continuous network availability.
    • Network Administrator
      Network Administrator
      Manage network devices, user access, and system performance while maintaining secure and stable network operations.
    • Network Automation Associate
      Network Automation Associate
      Implement automation tools and AI-driven workflows to simplify network management and improve operational efficiency.
    • Network Security Analyst
      Network Security Analyst
      Protect network infrastructure by identifying vulnerabilities, monitoring threats, and implementing security controls.

    Frequently Asked Questions

    The certification is suitable for networking professionals, IT specialists, cybersecurity analysts, students, and AI enthusiasts.

    Learners will develop skills in AI-driven network automation, monitoring, security, performance optimization, and modern network management.

    The program teaches how AI can be applied to networking, automation, cloud environments, IoT, and security operations.

    Learners should have basic knowledge of networking, Python, AI/ML fundamentals, and network management tools.

    Learners gain hands-on experience in AI-powered networking solutions through projects and case studies.

    Prerequisites

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    Exam Details

    Duration

    90 minutes

    Format

    50 multiple-choice/multiple-response questions

    Exam Blueprint

    Enterprise Networking Foundations & AI Workload Impact 4%
    Advanced Routing, Switching, and Data Center/AI Fabric Networking 10%
    Cloud Networking, SASE, and Hybrid Connectivity 10%
    Wi-Fi 7, Edge AI & IoT Networking 10%
    AI & Machine Learning Foundations for Network Engineers 10%
    Generative AI, RAG, and Prompt Engineering for Operations 10%
    Network Automation, IaC, and Agentic AI Workflows 10%
    AI-Enhanced Network Security and Zero Trust 10%
    Modern Observability: eBPF, OpenTelemetry, and AIOps 10%
    AI Governance, Responsible AI, and Sustainable Networking 8%
    Capstone Project - End-to-End AI Network Operations 8%
    Course Price: USD $495.00
    Self-Paced Online
    Purchase Self-Paced Course
    Instructor-Led (Live Virtual/Classroom)