LearnXOps: Full List of Topics Covered

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The LearnXOps course by Sandip Das covers a comprehensive range of topics in Cloud, DevOps, MLOps, and Machine Learning Platform Engineering. The full list of topics is available here: LearnXOps Full Topics List.

You Should Know:

To get the most out of Cloud, DevOps, and MLOps, here are some essential commands, tools, and practices you should master:

1. Cloud (AWS, Azure, GCP) Commands

  • AWS CLI (Install & Configure): 
    curl "https://awscli.amazonaws.com/awscli-exe-linux-x86_64.zip" -o "awscliv2.zip"
unzip awscliv2.zip
sudo ./aws/install
aws configure
  • Azure CLI (Install on Linux): 
    curl -sL https://aka.ms/InstallAzureCLIDeb | sudo bash
az login
  • Google Cloud SDK: 
    echo "deb [signed-by=/usr/share/keyrings/cloud.google.gpg] https://packages.cloud.google.com/apt cloud-sdk main" | sudo tee -a /etc/apt/sources.list.d/google-cloud-sdk.list
sudo apt-get update && sudo apt-get install google-cloud-sdk
gcloud init

2. DevOps Tools & Commands

  • Terraform (Infrastructure as Code): 
    wget https://releases.hashicorp.com/terraform/1.5.5/terraform_1.5.5_linux_amd64.zip
unzip terraform_1.5.5_linux_amd64.zip
sudo mv terraform /usr/local/bin/
terraform init
terraform apply
  • Kubernetes (kubectl): 
    curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl"
chmod +x kubectl
sudo mv kubectl /usr/local/bin/
kubectl get pods -A
  • Docker (Containerization): 
    sudo apt-get update
sudo apt-get install docker.io
sudo systemctl start docker
docker run hello-world

3. MLOps & Machine Learning

  • MLflow (Experiment Tracking): 
    pip install mlflow
mlflow ui --host 0.0.0.0
  • Kubeflow (ML on Kubernetes): 
    pip install kfp
kubectl apply -k "github.com/kubeflow/pipelines/manifests/kustomize/cluster-scoped-resources?ref=v2.0.0"
  • FastAPI (Model Deployment): 
    pip install fastapi uvicorn
uvicorn main:app --reload

What Undercode Say:

Mastering Cloud, DevOps, and MLOps requires hands-on practice with real-world tools. Automate deployments, manage infrastructure as code, and track ML experiments efficiently. The LearnXOps course provides structured learning—apply these commands to reinforce skills.

Prediction:

As AI-driven automation grows, MLOps and DevOps will merge further, requiring engineers to master both infrastructure and machine learning pipelines.

Expected Output:

  • AWS CLI configured
  • Terraform infrastructure deployed
  • Kubernetes cluster running
  • MLflow tracking server active
  • FastAPI model serving

IT/Security Reporter URL:

Reported By: Sandip Das – Hackers Feeds
Extra Hub: Undercode MoN
Basic Verification: Pass ✅

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