Network Automation, NetDevOps & AI
for Network Engineers
Learn LIVE with Sagar Dhawan — not a recorded video library. Build Python, Ansible, API, NetBox, pyATS/Genie and AI-powered automation through instructor demonstrations, EVE-NG labs and guided practice.
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Try AI Network Troubleshooting
See the type of workflow you will learn to build. Choose a network issue, inspect the CLI state and run the browser demo.
Free interactive simulation • No login required • No configuration is sent to a real device
In the live course, you learn how to connect structured network state, AI analysis, human approval, automation and pyATS validation—not just click a demo.
Learn LIVE With the Instructor
Every live class follows an engineering workflow: understand the concept, watch it built, execute the lab, troubleshoot failures and validate the result.
2 Classes Every Week × 3 Months
24 instructor-led sessions and 48 live hours. Ask questions during class, follow demonstrations and work through practical network automation labs.
See How We Teach Network Automation
Watch a real instructor-led automation demonstration before you enroll.
Stop Learning Automation as Disconnected Tools.
Python, Ansible, APIs and AI become valuable when you understand how they work together to build, change and validate real networks.
What You Will Build
Not just syntax exercises. Build automation workflows that resemble the work network automation engineers actually perform.
Multi-Device Backup System
Connect to network devices concurrently, collect configuration and operational state, handle failures and generate organized backups.
Configuration Generator
Turn structured YAML data into consistent multi-site configurations using Python and Jinja2.
API Health Collector
Authenticate to network APIs, collect inventory and health data and generate structured reports.
Ansible Branch Deployment
Build reusable playbooks and roles for repeatable network configuration and deployment.
NetBox-Driven Automation
Use NetBox as the source of truth and drive automation from structured network inventory.
pyATS Validation
Run pre-checks and post-checks so automation verifies network state instead of assuming a change succeeded.
AI Troubleshooting Assistant
Feed structured network state into an AI workflow for analysis, recommendations and human-approved remediation.
End-to-End Pipeline
Connect source of truth, automation, network testing, CI and AI into one enterprise-style workflow.
Learn the Tools as One Automation System
24-Class Hands-On Curriculum
Two live classes per week, two hours per class, designed to complete in approximately three months.
One Lab. Increasing Automation Maturity.
The same network evolves through the course, so every new tool solves a problem students already understand.
Source of Truth→Python + Ansible→R1 • R2 • R3
Network→pyATS / Genie→PASS / FAIL→AI Analysis
Configuration generation → multi-device deployment → operational-state collection → pyATS/Genie validation → AI-assisted troubleshooting → PASS / FAIL reporting.
Don’t Just Learn AI.
Learn How AI Works With Networks.
This is not a generic ChatGPT class. Learn the AI concepts that matter to network automation and testing, then apply them to network state, troubleshooting and controlled remediation.
From Manual Networking to Automation Engineering
Before the Course
- Manual CLI changes
- Copy/paste configurations
- Excel-based inventories
- Manual verification
- Repeated troubleshooting
- No automated network testing
- Unsure how AI applies to networking
After the Course
- Python-based automation
- API-driven networking
- Ansible deployments
- NetBox source of truth
- Automated pyATS validation
- Git and CI workflows
- AI-assisted troubleshooting
- Agentic automation concepts
Built for People Who Already Think Like Network Engineers
Network Engineers
Move from repetitive CLI operations to programmable workflows.
CCNA / CCNP / CCIE
Add automation and NetDevOps capabilities to strong networking fundamentals.
Security / NOC / Support
Automate collection, validation, troubleshooting and operational tasks.
DevNet / Infrastructure
Connect Python, APIs, source of truth, testing and AI into real workflows.
No advanced programming experience required. Networking fundamentals are recommended.
Sagar Dhawan
Network Automation & Infrastructure Trainer
14+ years across enterprise networking, security and automation. CCIE Security, CCNP Enterprise/Security and DevNet certified, with hands-on experience across Python, Ansible, pyATS, SD-WAN, Cisco enterprise/security platforms and multi-vendor network environments.
Student Feedback & Training Proof
Verified student feedback, LinkedIn recommendations and class clips will be published here. Until then, explore the live demo and free automation playground to evaluate the teaching approach yourself.
Designed to Fit Into 3 Months
Ready to Move From Network Engineer to Network Automation Engineer?
Build the Python, automation, testing, NetDevOps and AI skills around the networking knowledge you already have.
Frequently Asked Questions
Do I need Python experience?
No advanced Python experience is required. The program starts with Python concepts specifically needed by network engineers and progressively applies them to automation.
Is this suitable for CCNA or CCNP engineers?
Yes. Networking fundamentals are recommended. The course is designed for engineers who understand networking and want to add automation, NetDevOps and AI skills.
Will I learn Ansible network automation?
Yes. The live curriculum includes inventory, playbooks, variables, loops, network modules, Jinja2, roles, Vault and a branch-deployment lab.
Does the course cover AI for network engineers?
Yes. The AI module covers practical AI/ML foundations, Generative AI, prompt engineering, RAG, Agentic AI, local LLM concepts, Ollama, MCP concepts and network testing/troubleshooting use cases.
What is Agentic AI in network automation?
Students learn the concept of AI systems that can reason over network information and invoke controlled tools/workflows, while keeping human approval and automated validation in the loop.
Will I learn pyATS and Genie?
Yes. Students use pyATS/Genie for structured network state, pre-checks, post-checks and automated validation.
Does the course include NetBox?
Yes. NetBox is introduced as a network source of truth and integrated with Python and Ansible workflows.
Are NETCONF and RESTCONF covered?
Yes. A dedicated class introduces NETCONF, RESTCONF, YANG and model-driven network automation.
Is SD-WAN automation covered?
SD-WAN API automation and AI-assisted SD-WAN testing concepts are included as use cases/bonus material. The core course focuses on transferable automation skills.
Are labs included?
Yes. The course is designed around live demonstrations, hands-on labs, projects and an enterprise capstone.
Is this live or recorded?
The core program contains 48 hours of live instructor-led training. Additional technologies and exercises are provided as bonus/self-paced material where available.
What are the bonus modules?
Bonus topics include Paramiko, NAPALM, Scapy, Pyntc legacy labs, advanced Python/regex/Netmiko, additional Ansible and pyATS labs, Docker, Terraform, SD-WAN API automation, Catalyst Center API examples and AI prompt resources.
How long is the course?
The planned duration is approximately three months: 24 live classes, two classes per week and two hours per class.
Try Something Practical Before You Join
Three lightweight browser tools for network engineers. Nothing is sent to a production device and no API key is required.
CLI → Netmiko Starter
Enter show commands, one per line.
Generated Starter Code
Network AI Prompt Builder
Generated Prompt
Automation Pre-Check Builder
Select the change type.
Suggested Validation Workflow
Talk to Sagar Before You Enroll
Share your profile. Clicking submit opens WhatsApp with your details pre-filled so you can continue directly with the trainer.