Uncodemy vs Great Learning: Which DevOps Course Is Better?

DevOps · Course Comparison

Uncodemy vs Great Learning — Which DevOps Course Is Better?

SECTION 01How to compare Uncodemy and Great Learning fairly

Course comparisons online are often written by one of the two sides, so treat them carefully — including this one, which is published by Uncodemy. To keep it fair, we will not make claims about Great Learning's fees, trainers or outcomes. Those change and you should check them directly on their website and in a counselling call.

What we can do is give you the same yardstick for both. DevOps is a hands-on discipline, so the real question is not which brand is bigger but which course will have you building pipelines, writing Dockerfiles and debugging Kubernetes deployments every week.

Uncodemy DevOps course — what to expect

Format       : Trainer-led batches; classroom in Noida
               and live online options
Batches      : Weekday and weekend batches
Practice     : Hands-on DevOps labs (confirm the
               current tool list in the syllabus)
Support      : Resume rebuilds, portfolio review,
               mock interviews, interview scheduling
Missed class : Ask about batch repeat policy

Always confirm current fees and batch dates
with a counsellor before enrolling.

Questions to ask Great Learning (or any platform)

1. Is the DevOps programme live, recorded or a mix?
2. Which tools are covered, and in how much depth?
3. Are cloud lab environments provided, and for how long?
4. Who reviews my projects, and how quickly?
5. Is there a university or partner certificate?
6. What career support is included, exactly?
7. What is the total fee and refund policy, in writing?

SECTION 02DevOps syllabus depth: what both should cover

Whichever course you choose, a 2026 DevOps syllabus should take you from Linux basics to deploying a containerised application on Kubernetes with an automated pipeline. If either option skips a major block, factor in the time you will spend learning it alone.

Pay special attention to infrastructure as code and monitoring. Many short courses stop at Docker and Jenkins, but job descriptions increasingly mention Terraform, Prometheus and Grafana as well.

# Dockerfile for a small Python web app
FROM python:3.12-slim

WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

COPY . .
EXPOSE 8000
CMD ["gunicorn", "--bind", "0.0.0.0:8000", "app:app"]

# Build and run locally:
#   docker build -t myapp:1.0 .
#   docker run -p 8000:8000 myapp:1.0

# .github/workflows/ci.yml
name: ci
on:
  push:
    branches: [main]
jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - name: Run tests
        run: |
          pip install -r requirements.txt
          pytest
      - name: Build image
        run: docker build -t myapp:${{ github.sha }} .

SECTION 03Format, support and value: who should pick which

Format is where the two options differ most. A trainer-led batch with classroom access suits learners who benefit from fixed timings, face-to-face doubt solving and peers working on the same lab at the same time. A mostly online platform suits learners who are self-motivated and need to fit study around a job or other commitments.

Value is not the same as the lowest fee. A cheaper course you abandon halfway is more expensive than a course you actually finish with a working project. Think about how you have learned best in the past — that is the most reliable predictor of which format will work now.

# deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: myapp
spec:
  replicas: 2
  selector:
    matchLabels:
      app: myapp
  template:
    metadata:
      labels:
        app: myapp
    spec:
      containers:
        - name: myapp
          image: myapp:1.0
          ports:
            - containerPort: 8000

# Apply and inspect the deployment
kubectl apply -f deployment.yaml
kubectl get deployments
kubectl get pods -l app=myapp

# Expose it inside the cluster
kubectl expose deployment myapp --port=80 --target-port=8000

# Debug a failing pod
kubectl describe pod <pod-name>
kubectl logs <pod-name>

SECTION 04Side-by-side DevOps course scorecard

Fill this in after attending a demo or counselling session with each provider. Score both on identical criteria before looking at the totals.

DEVOPS COURSE SCORECARD (1-5 each)

Criterion                      Uncodemy   Great Learning
-----------------------------  ---------  --------------
Format suits my schedule         __          __
Hands-on lab environment         __          __
Linux + scripting depth          __          __
CI/CD depth                      __          __
Docker + Kubernetes depth        __          __
Cloud + Terraform coverage       __          __
Doubt support speed              __          __
Career support                   __          __
TOTAL (out of 40)                __          __

LAB CHECKLIST — ask to see each one

[ ] A Linux server I can SSH into
[ ] A Git repository I push to
[ ] A CI pipeline I write myself
[ ] Docker images I build and run
[ ] A Kubernetes cluster (local or cloud)
[ ] Terraform code that creates real resources
[ ] Monitoring dashboard (Prometheus / Grafana)

DECISION NOTE

I learn best when: ____________________
My weekly study time: ____ hours
Higher score: ____________  (__ / 40)
Does the higher score also fit my learning style? Yes / No
Final choice: ____________
First project I will build: ____________

SECTION 05Tips before choosing a DevOps course

Use these checks before paying for any DevOps programme:

• Try Linux first — spend a week on the command line; if you enjoy it, DevOps is likely a good fit.
• Ask for the lab, not the brochure — a two-minute look at a real lab tells you more than a long feature list.
• Compare module depth — a course that gives Kubernetes one session is not the same as one that gives it two weeks.
• Check support hours — find out who answers doubts and how fast, especially for weekend learners.
• Ignore guarantees — treat any promise of a guaranteed job as a reason to ask more questions.

SECTION 06Interview Q&A — DevOps after any course

SECTION 07Test yourself — choosing a DevOps course

SECTION 08Frequently asked questions

SECTION 09Related reads