By completing this course, you will be able to: 

• Apply AI and machine learning concepts to modern networking  

• Understand AI-driven network automation and orchestration  

• Use AI for network monitoring, anomaly detection, and predictive maintenance  

• Apply AI techniques to network performance optimization  

• Understand AI-enhanced network security and threat mitigation  

• Explore the integration of AI with cloud, IoT, 5G, SDN, and NFV  

• Apply AI networking concepts through practical projects and case studies

Module 1: Networking Foundations 

• Network types and topologies  

• Networking components and protocols  

• IP addressing  

• VLANs  

• Wireless standards  

• Essential network security concepts  

Module 2: Advanced Networking Technologies

• VLANs  

• Software-Defined Networking (SDN)  

• Network Functions Virtualization (NFV)  

• 5G  

• Internet of Things (IoT)  

• Edge computing  

• Advanced routing  

• Data centers  

• Cloud networking  

Module 3: AI in Networking

• AI and machine learning applications in networking  

• Traffic analysis  

• Network optimization  

• Anomaly detection  

• Network automation  

• Predictive maintenance  

Module 4: Network Automation and Orchestration

• Automation tools  

• Python scripting  

• APIs  

• AI-driven orchestration  

• Intent-based networking  

• Kubernetes  

• Zero Trust architecture  

Module 5: AI-Enhanced Network Security

• AI-based threat detection  

• Incident response  

• Secure network design  

• SIEM enhancement  

• Predictive analytics  

• AI security considerations  

Module 6: Practical Labs and Hands-On Projects 

• Network simulation  

• AI-driven network automation  

• Threat detection models  

• Security implementation  

• AI-enhanced network design projects  

Module 7: Emerging Trends and Future Directions

• AI in 5G  

• Quantum computing impacts  

• AI-powered IoT networks  

• Blockchain security  

• Future opportunities in AI networking 

• Instructor-Led: 5 days  

• Self-Paced: 40 hours of content

Practical learning includes: 

• AI-driven network automation  

• Network simulation  

• Automated network monitoring  

• Anomaly detection  

• Predictive maintenance  

• AI-enhanced network security  

• Threat detection models  

• AI-powered network design  

Tools explored: Ansible, Puppet, Chef, REST APIs, NETCONF, Kubernetes, OpenStack, GNS3, and Cisco Packet Tracer.

• Exam Duration: 90 minutes  

• Questions: 50  

• Passing Score: 70% (35/50)  

• Format: Multiple-choice questions  

• Delivery: Online proctored examination  

• Retake: One free retake

• Networking Foundations — 13%  

• Advanced Networking Technologies — 16%  

• AI in Networking — 16%  

• Network Automation and Orchestration — 16%  

• AI-Enhanced Network Security — 13%  

• Practical Labs and Hands-On Projects — 13%  

• Emerging Trends and Future Directions — 13%

• Networking professionals  

• Network administrators  

• System administrators  

• IT specialists  

• Cybersecurity analysts  

• AI enthusiasts  

• Students and fresh graduates  

• Professionals working with cloud and IoT environments

• Foundational networking knowledge  

• Familiarity with Python programming  

• Fundamental understanding of AI and machine learning  

• Familiarity with network management tools is beneficial