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apiVersion: argoproj.io/v1alpha1
kind: Workflow
metadata:
  generateName: vote-ci-
spec:
  entrypoint: main
  arguments:
    parameters:
    - name: repo-url
      value: "https://github.com/xxxxxx/vote.git"

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Setting up Argo Locally on existing Kubernetes Cluster

Create Argo Namespace

kubectl create namespace argo
kubectl get ns

Setup Argo Version and Install it

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Does an AI Platform Engineer Need Data Science Essentials?

Short Answer: Yes, but only selectively.

As an AI Platform Engineer, the focus is on building, deploying, and optimizing AI/ML models at scale, not on developing new ML algorithms or performing deep data science research. However, to work effectively with Data Scientists and MLOps workflows, an AI Platform Engineer should understand key Data Science essentials related to:

✅ Understanding ML model workflows (How data moves through AI/ML pipelines)
✅ Feature Engineering & Feature Stores (How data is prepped for models)
✅ Fine-tuning & Inference Optimization (How models are trained and served efficiently)
✅ Evaluating Model Performance (Ensuring models meet production-quality standards)

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Mini Project Spec: Host Your Resume on AWS S3

Introduction:

In this mini-project, you will learn how to use Amazon S3 to host your resume, creating a publicly accessible web-based version of your professional profile. This is a practical skill that can be applied in real-world scenarios, such as job applications or networking events.

Project Goal:

• To host an HTML version of your resume on AWS S3.

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#!/bin/bash
sudo su
curl -O https://raw.githubusercontent.com/wp-cli/builds/gh-pages/phar/wp-cli.phar
chmod +x wp-cli.phar
sudo mv wp-cli.phar /usr/local/bin/wp
wp transient delete --all --path=/srv/www/wordpress --allow-root
wp option get siteurl --path=/srv/www/wordpress --allow-root
wp option get home --path=/srv/www/wordpress --allow-root

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name: Test and Trigger Databricks Job

# Trigger the workflow on push to the main branch
on:
  push:
    branches:
      - main

jobs:
  test:

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import pytest
import Mixed_Language_Demo as databrics_code  # Import the module

def test_dataframe_creation():
    """
    Test for the `create_dataframe` function
    """
    # Create the DataFrame
    df = databrics_code.create_dataframe()

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name: Test Notebook Code

# Trigger the workflow on push events to all branches
on:
  push:
    branches:
      - '*'

jobs:
  test:

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#!/bin/bash

echo "I: Installing Apache and PHP ..."

sudo apt update
sudo apt install -yq apache2 \
                 ghostscript \
                 libapache2-mod-php \
                 mysql-client \
                 php \

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<IfModule mod_rewrite.c>
RewriteEngine On
RewriteRule .* - [E=HTTP_AUTHORIZATION:%{HTTP:Authorization}]
RewriteBase /
RewriteRule ^index\.php$ - [L]
RewriteCond %{REQUEST_FILENAME} !-f
RewriteCond %{REQUEST_FILENAME} !-d
RewriteRule . /index.php [L]
</IfModule>