The course provided me with a solid understanding of IT service desk operations and troubleshooting techniques. It has improved my ability to handle user issues with confidence and professionalism.
AI+ Network Practitioner™
AT-510
Validate Your Expertise in Networking: Harness AI for Automation, Security, and Next-Generation Efficiency
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.
- High-Quality Video, E-book & Audiobook
- Modules Quizzes
- AI Mentor
- Access for Tablet & Phone
- Online Proctored Exam with One Free Retake
- Hands-on Practices
Why This Certification Matters
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Comprehensive Knowledge Covers fundamental networking concepts and advanced AI-driven technologies like SDN and NFV.
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AI-Powered Efficiency Exam assesses knowledge of how AI can optimize network performance, automation, and security
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Practical Application Assessment Exam includes scenario-based questions for real-world application of AI in networking.
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Future-Ready Skills Validates competency to adapt to the rapidly evolving AI-enhanced networking landscape.
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Leadership Opportunities Validates competency for leadership roles in the AI and networking fields.
At a Glance: Course + Exam Overview
Program Name
AI+ Network Practitioner™
Included
Instructor-led OR Self-paced course + Official exam + Digital badge
Prerequisites
Basic networking, Python, AI/ML fundamentals, and familiarity with network management tools.
Exam Format
50 questions, 70% passing, 90 minutes, online proctored exam
Delivery
Online labs, projects, case studies
Outcome
Industry-recognized credential + hands-on experience
Who Should Enroll?
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Networking Professionals: Looking to advance your skills by integrating AI into network design, automation, and security to stay ahead in a competitive field.
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AI Enthusiasts: Interested in applying AI technologies like ML and automation Specifically, networking domains.
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IT Specialists: Focused on exploring the intersection of cloud computing, IoT, and AI to optimize infrastructure and network performance.
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Students and Fresh Graduates: Pursuing careers in AI, cybersecurity, or networking and wanting to gain hands-on experience and credentials to strengthen their professional profile.
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Cybersecurity Analysts: Seeking to utilize AI-driven solutions for threat detection, network protection, and predictive analytics.
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System Administrators: Eager to transition into roles involving network automation, orchestration, and AI-based tools for managing complex systems.
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Tech Innovators and Researchers: Interested in exploring emerging trends like 5G, edge computing, or blockchain in AI-enhanced networking.
Skills You'll Gain
AI-driven network automation and orchestration.Automated network monitoring and anomaly detection.Predictive maintenance and fault prevention.AI-enhanced network security and threat mitigation.Network performance optimization using AI methods.Working with cloud, IoT, and modern network environments.Understanding how AI combines with current networking technologies.
What You'll Learn
- 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.
- 1.1 Basic Networking Concepts
- 1.2 Network Infrastructure and Design
- 1.3 Introduction to Network Security
- 1.4 AI Workload Networking Overview
- 2.1 Advanced Routing and Switching
- 2.2 Data Center and AI Infrastructure Networking
- 2.3 High-Performance AI Fabric Considerations
- 2.4 Quality of Service (QoS) for Application and AI Workloads
- 3.1 Network Virtualization and Cloud Networking Models
- 3.2 SD-WAN and Hybrid Multi-Cloud Connectivity
- 3.3 SASE and SSE with AI
- 4.1 Wi-Fi 7 and AI-Driven RF Optimization
- 4.2 Edge Computing, Fog Networking and IoT Models
- 4.3 Edge AI and Small Language Models
- 4.4 Wi-Fi 7 + Edge AI Use Cases and Architecture
- 5.1 AI and Machine Learning Fundamentals
- 5.2 AI-Driven Network Optimization
- 5.3 Operational Limits of AI Recommendations
- 5.4 Predictive Network Maintenance
- 6.1 Generative AI and LLM Concepts for Network Operations
- 6.2 RAG (Retrieval-Augmented Generation) for Network Knowledge
- 6.3 Prompt Engineering for Network Engineers
- 7.1 Fundamentals of Network Automation & Infrastructure as Code (IaC)
- 7.2 Network APIs and Programmability
- 7.3 Agentic AI, Function Calling, and MCP
- 7.4 ChatOps and Operational Workflows
- 7.5 Use-Cases and Case Studies
- 8.1 AI-Enhanced Threat Detection
- 8.2 Secure Network Design and Zero Trust
- 8.3 SIEM, SOC, and AI-Assisted Security Operations
- 8.4 Adversarial AI and AI Security Risks
- 8.5 Use-Cases and Case Studies
- 9.1 Modern Observability Foundations (Metrics, Logs, and Traces)
- 9.2 eBPF for Deep Network Visibility
- 9.3 OpenTelemetry and Streaming Telemetry Standards
- 9.4 AIOps: Alert Correlation, Noise Reduction, and Root Cause Support
- 9.5 Use-Cases and Case Studies
- 10.1 AI Governance and Responsible Network Operations
- 10.2 Privacy, Data Handling, and Bias in Network AI
- 10.3 Sustainable/Green Networking with AI
- 10.4 Future Network Operations
- 10.5 Use-Cases and Case Studies
- 11.1 Capstone Objective
- 11.2 Capstone Scenario
- 1.1 What Are AI Agents
- 1.2 Applications and Trends of AI Agents in Network Intelligence
- 1.3 How Does an AI Agent Work
- 1.4 Characteristics of AI Agents
- 1.5 Types of AI Agents
Tools You'll Master
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 Details
Duration
90 minutes
Passing Score
70% (35/50 Correct)
Format
Multiple Choice Questions (MCQ)
Delivery Method
Online via proctored exam platform
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%
Choose the Format That Fits Your Schedule
What's Included (One-Year Subscription + All Updates):
- High-Quality Videos, E-book (PDF & Audio), and Podcasts
- AI Mentor for Personalized Guidance
- Quizzes, Assessments, and Course Resources
- Online Proctored Exam with One Free Retake
- Comprehensive Exam Study Guide
- Access for Tablet & Phone
Instructor-Led (Live Virtual/Classroom)
- 5 days (live or virtual) Self-Paced: 40 hours of content
- Real-time Q&A, peer collaboration, and hands-on labs
- Led by AI Certified Trainers and delivered through Authorized Training Partners
Self-Paced Online
- 40 hours of content
- Learn anywhere, anytime, with modular quizzes to track progress
Need More Flexibility?
To help you along your way, we can help you set up a customizable payment plan. Just book a call, we’ll provide you with the details!
Let's Arrange a Call9/10 of our learners achieve their learning objectives after successful completionProcess Advisors
The course gave me a clear understanding of network security concepts and practical exposure. It helped me build confidence in handling real-world security tasks.
My path to cloud architecture had its hurdles, but Fortray was there every step of the way. They provided valuable insights into cloud technologies and architectural design. With their guidance, I turned challenges into opportunities, and today, as a Cloud Architect, I help organizations leverage the cloud for their growth and success.
The path to becoming a Cybersecurity Engineer felt like decrypting an impossible algorithm—until Fortray provided the key. Their mentorship was like a robust IPS, detecting and eliminating my weaknesses while optimizing my strengths. Now, I stand as a protector in the ever-evolving IT landscape, proud to carry their legacy forward.
This course strengthened my full-stack development skills and practical understanding. I am more confident in building and managing complete web applications.
This course improved my understanding of project management methodologies and workflows. I gained practical skills to plan and execute projects effectively.
The course provided valuable hands-on experience in data analysis tools and techniques. It enhanced my ability to extract meaningful insights from data.
The training helped me build strong analytical skills and understand how to work with real-world data science problems effectively.
The course helped me understand automation testing frameworks and best practices. I gained practical experience in writing and executing automated test cases.
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.
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