Cloudsoft runs fully live, instructor-led online batches for every track we teach in our Hyderabad classroom — AWS, Azure, GCP, DevOps, Python, ML, Citrix, SRE and Linux. Same trainer. Same curriculum. Same placement coordinator. You join from wherever you are (we've had students log in from Warangal, Sharjah, Toronto and everywhere in between), and you get a real cloud lab on day one with the bill paid by us.
Online training gets a bad rap, and honestly, most of it is deserved. The market is flooded with recorded drip-feeds dressed up as courses, with no trainer to ask, no cohort to belong to, and no idea what to do once the videos end. Our online batches are built to fix exactly that. Everything below is what separates a Cloudsoft live online class from a Udemy playlist.
Every single class is a real human trainer, teaching in real time, answering your question the minute you ask it. We never re-sell recordings dressed up as a course. You raise your hand in the Zoom chat, the trainer stops, explains, then moves on. Same room, just digital.
AWS, Azure and GCP sandbox accounts come included. No credit card needed from your side. You build real VPCs, real Kubernetes clusters, real MLOps pipelines — we pay the cloud bill, you keep the code on your own GitHub.
Every session is posted to your LMS within a few hours. Watch it on the bus, at 2am before an interview, or three years from now when you need to remember how IAM policies actually work. You own the playlist forever.
The course Slack and AI tutor are both live 24/7. Trainers drop in between sessions, alumni answer from their own jobs, and our AI assistant has read every lab guide — so when you hit a weird Terraform error at 11pm, there's always someone who has already solved it.
Tier-2 town, Gulf shift, night-time in Toronto — doesn't matter. We have morning, evening and weekend batches in IST, and over 40% of our online students currently live outside Hyderabad. Your internet just needs to hold a Zoom call; we handle the rest.
Online students get the same placement support as classroom students. Same resume clinic. Same mock-interview panel. Same direct hiring-manager intros. The only thing that changes is the commute.
Here's an honest look at a weekday evening. At 6:55 PM, students start filing into the Zoom room — some from their desks at an office, some from a kitchen table, some on a phone in the car while waiting for a partner to finish shopping. At 7:01, our trainer opens with a five-minute recap of the previous session and asks two random students to summarise what they remember. Nobody is called out for being wrong; the point is to keep you awake and honest about where you stand.
The next 20 minutes are concept teaching on a shared whiteboard — IAM trust policies, EKS pod networking, whatever is on the plan for the day. The trainer draws, talks, flips back to old diagrams, and the chat fills up with questions that get answered in real time. Then the lab starts. Everyone switches to their own sandbox account; the trainer is pair-programming on the main screen; students drop screenshots and error messages into the chat whenever something refuses to work. It does not sound glamorous. It is exactly the rhythm that makes people ship.
The last 15 minutes are what we call stand-up — we go around the virtual room, camera-on if you want, and every student says out loud what they got working, what they broke, and what they still don't understand. That one habit, repeated every session, is probably the single biggest reason our online cohorts retain material after finishing. You can't hide from a stand-up. And you shouldn't want to.
Classes run on Zoom because it is the one platform that still works on every device, every browser and every network we have tested — including the flakier ones in tier-2 cities and the Gulf. We layer our own learning portal on top. When you enrol, you get login credentials to the LMS where the live link, the recordings, the lab guides, the quizzes, the capstone project briefs, the Slack invite and the AI tutor all live under one roof. No switching tabs to find what you need.
Labs are where we differ most from the low-cost training market. Every student gets a dedicated sandbox on the relevant cloud — AWS for the AWS + DevOps track, Azure for the Admin track, GCP for the Vertex AI track. The sandbox is funded by Cloudsoft, quota-capped so you cannot accidentally rack up a bill, and reset automatically between weeks. If your track involves more than one cloud (Multi-Cloud DevOps, for example), you get sandboxes on all three. Infrastructure like EKS clusters, AVD hosts and MLOps pipelines are real; nothing is simulated.
On top of the live class, you get a 24/7 AI tutor that has been fine-tuned on every lab guide and capstone project we teach. It is surprisingly good at the specific things that stump people at 11 PM — why a pod is stuck in CrashLoopBackOff, why an IAM role assumption is failing, why Terraform keeps planning in a loop. If the AI can't help, our Slack is staffed by trainers and senior alumni; most questions get answered within 30 minutes, even late at night.
Every track runs a weekday batch and a weekend batch in parallel, so you can almost always find a slot that fits your life. Timings are in Indian Standard Time — if you're in a different zone, our admissions desk can recommend the best fit. Every online track is flat-priced at ₹15,000, no surprise add-ons.
| Track | Duration | Online slots (IST) | Next start | Enrol |
|---|---|---|---|---|
| AWS Solutions Architect + DevOps | 60 hrs | Mon–Fri · 7:00 AM / 7:30 PM IST | 27 Apr 2026 | Reserve → |
| Azure Admin + AVD + Intune | 55 hrs | Mon–Fri · 7:00 PM IST | 28 Apr 2026 | Reserve → |
| Google Cloud + GKE + Vertex AI | 50 hrs | Tue–Fri · 8:00 PM IST | 02 May 2026 | Reserve → |
| Multi-Cloud DevOps | 80 hrs | Weekend · 10:00 AM IST | 03 May 2026 | Reserve → |
| Python Fullstack + ML + Data | 80 hrs | Mon–Fri · 8:30 AM IST | 29 Apr 2026 | Reserve → |
| Citrix Virtual Apps & Desktops | 50 hrs | Mon–Fri · 8:00 PM IST | 30 Apr 2026 | Reserve → |
| DevOps: K8s, Docker, Jenkins | 45 hrs | Mon–Fri · 7:30 AM IST | 05 May 2026 | Reserve → |
| Machine Learning & MLOps | 70 hrs | Weekend · 2:00 PM IST | 10 May 2026 | Reserve → |
| Linux Administration + Shell | 35 hrs | Mon–Fri · 6:00 AM IST | 26 Apr 2026 | Reserve → |
| SRE & Observability | 65 hrs | Weekend · 10:00 AM IST | 17 May 2026 | Reserve → |
This is the part that trips most online learners up — they finish the course and realise the "placement support" promised on the landing page was a five-line email template. That isn't what happens here. Online students get the same dedicated placement coordinator, the same resume review schedule, the same mock interview panels, and the same direct referrals as our classroom students. Median time from course completion to offer letter is 45 days across our cloud tracks — and the split is almost identical for online and classroom cohorts.
The partner network matters too. Our 2,000+ hiring partners include consulting heavyweights like Accenture, TCS, Infosys, Wipro, HCLTech, Tech Mahindra, Cognizant, Capgemini, Deloitte, PwC, IBM and Virtusa, plus product MNCs like Microsoft, Amazon, Google, Dell, Cisco, Oracle, Optum, HPE, Siemens and Ericsson. Recruiters from roughly half these companies join our Zoom drives directly — you interview without ever touching a job portal.
We do not price online training differently from our classroom batches, because the trainer, the labs, the recordings and the placement support are exactly the same. Every track — AWS, Azure, Google Cloud, DevOps, Python Fullstack + ML, Citrix, Machine Learning and MLOps, Linux Administration, SRE & Observability, and the Multi-Cloud bundle — is a flat ₹15,000.
We run a referral credit of ₹1,500 per successful friend, a 15% group discount for three or more enrolling together, and a scholarship programme for career switchers who genuinely need the help. No hidden fees, no "placement fee," no exam-voucher upsell, no premium tier that mysteriously unlocks the real content.
Most of our online students fall into one of four buckets — and if you can see yourself in any of them, you're probably in the right place. The largest group is working professionals in their mid-20s to mid-30s who already have a job (often a support or manual-QA role) and are switching into cloud or DevOps. They pick the 7:00 PM weekday slot, show up after work, and the whole cohort ends up feeling like an online sprint team by month two.
The second group is recent graduates from tier-2 and tier-3 cities — Warangal, Vijayawada, Vizag, Guntur, Tirupati, Nellore, Rajahmundry, Kakinada and beyond — who need the Cloudsoft placement network but can't relocate to Hyderabad just yet. For these students, weekend batches plus heavy weekday self-study are the sweet spot, and most land their first offer before they have to think about relocating. The third group is parents returning to tech after a career break; the fourth is the overseas cohort (Gulf, UK, Canada, US) who want the trainer quality of Hyderabad but the flexibility of studying while holding a full-time visa job abroad.
If you don't fit neatly into any of those — that's fine too. We've had a plumber, a dentist, an army captain and a published poet finish our AWS + DevOps track in the last two years. The thing they had in common was being willing to show up live twice a week and put in an honest five hours of lab time. If that sounds like you, the rest works itself out.
Fully live. Every session is taught in real time by a human trainer on Zoom. You can un-mute, ask questions, share your screen to show a failing error, and get an answer inside the same session. Recordings are a bonus — posted after class so you can rewatch — but the class itself is always live.
YouTube and Udemy are great if you're allergic to being taught. But when the Terraform plan fails at 9pm and your next interview is on Thursday, a video doesn't help. Our online classes give you a trainer, a cohort of other learners, a placement coordinator, and a 24/7 tutor — all the things a pre-recorded course deliberately skips because they're expensive. That's also why Cloudsoft students place faster.
Anything that can run a stable 720p video call is enough. We've had students attend from village Wi-Fi, mobile hotspots and coffee shops without issues. If your internet drops mid-session, you pick up from the recording. Nobody gets left behind for a bandwidth hiccup.
Most weekday batches run 90 minutes per session, five days a week. Weekend batches are a longer 3-hour slot twice a week. Total course duration ranges from 35 hours (Linux) to 80 hours (Python Fullstack + ML, Multi-Cloud DevOps).
Morning (6:00 – 8:30 AM IST), daytime (8:30 – 10:00 AM IST), evening (7:00 – 8:30 PM IST, 8:00 – 9:30 PM IST) and weekend (10:00 AM – 1:00 PM IST, 2:00 – 5:00 PM IST). Over 60% of our working professionals pick the 7:00 PM weekday slot because they can join the minute they shut their laptop at work.
Flat ₹15,000 per track — the same as our classroom fee. There is no premium or discount for going online. AWS, Azure, GCP, DevOps, Python, ML, Citrix, SRE — all priced identically. Group enrolment of three or more gets 15% off.
We give you a sandbox account on day one — fully funded by Cloudsoft. You never pay a paisa to AWS, Azure or GCP for coursework. Build, break, re-build as much as you want; the bill is ours. You can still use a personal cloud account if you already have one, but it's optional.
Yes — and it happens more often than you'd expect. The online and classroom batches are taught by the same trainer, on the same curriculum, at overlapping times. If you're in Hyderabad for a week, tell your placement coordinator and we'll reserve your seat at the Ameerpet campus.
Our placement network is strongest across India, but yes — we support overseas alumni. Roughly 8% of our online students are based in the Gulf, Europe, Canada and the US, and we've helped them land roles at Optum, Accenture, Cognizant and a handful of Dubai-based cloud consultancies through our partner pipeline. Overseas placements typically take longer because the sponsor-visa factor, but we stay with you until you're hired.
Life happens. Every session is recorded and uploaded to your LMS within a few hours, and your trainer does a 10-minute recap at the start of the next class. If you miss more than two consecutive classes, tell us — we'll quietly shift you into the next parallel batch with no extra fee.
Pick a track, sit through a free 20-minute demo session with the trainer (no sales pitch, no pressure), and if you like what you see, pay online and you're in the next cohort. The whole onboarding takes less than a day from first call to first class.
Pick any upcoming batch, join with camera off if you'd prefer, watch the trainer teach for twenty real minutes, then decide. No sales pitch on the call, no follow-up spam, no sunk cost. If it's for you, we'll tell you what to do next. If it isn't, we'll tell you that too.