Nrdyn's academy offers hands-on certification training for RHCSA, RHCE, Ansible, CCNA, NVIDIA Agentic AI (NCP-AAI), AWS Solutions Architect, and GCP. Taught by working engineers, built around exam-style labs, and aimed at skills you can use the next day.
Showing all 7 certifications
Train for the NVIDIA-Certified Professional: Agentic AI (NCP-AAI) certification: building, deploying, and operating agentic AI systems on NVIDIA's stack, taught by engineers who run agents in production.
The best RHCSA prep is hands-on. Our EX200 course drills Linux administration, storage, users, services, and SELinux with exam-style labs.
Become a Red Hat Certified Engineer with automation at the core: Ansible, advanced administration, and the EX294 performance exam.
Practical Ansible from playbooks to roles and inventories, with automation patterns for real infrastructure at scale.
Cisco CCNA covering networking fundamentals, IP connectivity, security, and automation. Most learners certify in 8–12 weeks.
One of the most in-demand cloud certs. Core AWS services, well-architected design, security, and cost optimization with hands-on labs.
Google Cloud prep spanning Associate Cloud Engineer and Professional Cloud Architect tracks, with hands-on labs on real GCP projects.
A quick comparison of typical prep time and who each certification is for.
| Certification | Typical prep | Best for |
|---|---|---|
| Red Hat | ||
| RHCSA (EX200) | 4–6 weeks | New Linux administrators |
| RHCE (EX294) | 5–7 weeks | Admins moving to automation |
| Networking | ||
| CCNA (200-301) | 8–12 weeks | Networking beginners |
| AI | ||
| Agentic AI (NCP-AAI) | 4–6 weeks | AI & ML engineers |
| Cloud | ||
| AWS SAA (SAA-C03) | 6–8 weeks | Cloud architects |
| GCP (ACE / PCA) | 6–10 weeks | Google Cloud teams |
Typical preparation time and audience by certification.
It depends on where you already are. If you administer Linux, start with RHCSA. If you are new to infrastructure altogether, CCNA gives you the networking foundation everything else assumes. If you work with cloud already, go straight to AWS Solutions Architect Associate or the Google Cloud track. If you build with models and want the operational half, the NVIDIA Agentic AI track is the one. Tell us your starting point and we will say honestly which fits.
The seven tracks run from roughly 24 hours of instruction and labs for Ansible up to about 60 for CCNA, and typical preparation runs four to twelve weeks alongside a job. The comparison table above gives the prep time and intended audience for each certification side by side.
Both. Every track is delivered live online or onsite, with self-paced lab time between sessions. Onsite and private-cohort delivery can be run against your own environment, which is usually where the labs earn the most.
Yes. Private cohorts are the common case — a team takes one track together, or splits across two so the networking and cloud sides progress in parallel. Tell us the team size and the goal and we will recommend a track, or a combination, and hold the seats.
No. Every track runs its labs on provisioned environments — virtual network topologies for CCNA, live systems for the Red Hat tracks, cloud projects for AWS and GCP, and GPU environments for the NVIDIA track. Working in your own environment is an option, not a requirement.
Tell us your goals and team size. We'll recommend a track, or a combination, and hold the seats.