Networking, cloud, automation and AI infrastructure
Hands-on training on real enterprise equipment, from routing and automation to the GPU and AI infrastructure stack, with internship tracks that end in production-style project work.
3,000+ engineers trained · 890+ placed · 50+ hiring partners
A training institute paired with an engineering division that designs, deploys and secures production enterprise networks.
CCNA and CCNP through security, cloud, Linux, Python and automation, and on into the GPU and AI infrastructure stack. Every module is taught on equipment, not slides.
12 courses
Three career paths: enterprise networking, data center operations, and data center with automation. Each ends in real-time project work.
3 tracks
Our engineers work alongside yours on a live project, from design review through rollout.
Engineer-led
Network architecture, implementation, managed services, a 24/7 NOC, security and firewall deployment, plus IT staffing. The same engineers who run these networks teach the labs.
Engineering division
Every course page carries its fee, its full syllabus and what it prepares you for.
Each track bundles its courses, real-time project work and placement support into one programme. Take one, or all three together.
NOC to Network Engineer career path, L1 to L3 roles
$1,199
One-time. Programme access runs for a year.
Enterprise infrastructure, L1 to L3 operations
$1,499
One-time. Programme access runs for a year.
Advanced track: cloud, DevOps, network automation and AI-ready infrastructure
$1,799
One-time. Programme access runs for a year.
Best value
All three internships, taken as one sequence
$2,299$2,99923% off
One-time. Programme access runs for a year.
Founded in 2024 in Kurnool. Training delivered live online and on-site, on real enterprise hardware.
About the companyInstructors manage production enterprise estates, and the CTO spent eight years as a Palo Alto TAC engineer. The syllabus tracks what those networks actually run.
Real Cisco, Palo Alto and Aruba hardware in enterprise labs. Online students get virtual rack access to the same environments.
Wireshark analysis runs through the training rather than being bolted on at the end. You learn to read what the wire is doing.
What actually carries an AI workload: GPU cluster fabrics, RDMA and lossless Ethernet, non-blocking spine-leaf design, and the power, cooling and storage density a GPU rack demands. Taught as infrastructure, which is what a network engineer is hired to run.
Python, Netmiko, Ansible, REST APIs and CI/CD pipelines run against real devices, and they start from first principles. Networking knowledge is the prerequisite, not software experience.
The engineering division designs, deploys and secures production networks for enterprises. It is why the training stays current.
Enterprise servicesSee the labs, the syllabus and the equipment before you commit to anything.
