data-engineering-journey/_config.yml at main · maree217/data-engineering-journey · GitHub

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# GitHub Pages configuration for Data Engineering Journey

# Site settings
title: "Data Engineering Journey"
description: "Complete hands-on course: Traditional Data → Modern Engineering → AI-Driven Systems"
baseurl: "" # the subpath of your site, e.g. /blog
url: "https://your-username.github.io" # the base hostname & protocol for your site

# Course information
course:
  name: "Data Engineering Journey"
  subtitle: "From Traditional to AI-Driven Systems"
  version: "1.0.0"
  phases: 3
  duration: "12 weeks"

# Author information
author:
  name: "Data Engineering Course"
  email: "support@dataengineering.course"
  github: "your-username"

# Social media
social:
  github: "your-username/data-ai-course"
  discussions: "https://github.com/your-username/data-ai-course/discussions"

# Build settings
markdown: kramdown
highlighter: rouge
theme: minima

# GitHub Pages settings
plugins:
  - jekyll-feed
  - jekyll-sitemap
  - jekyll-seo-tag

# Collections
collections:
  phases:
    output: true
    permalink: /:collection/:name/

# Exclude files from processing
exclude:
  - .devcontainer/
  - scripts/
  - data/
  - node_modules/
  - .gitignore
  - package.json
  - package-lock.json
  - requirements.txt
  - "*.py"
  - "*.sh"
  - Gemfile
  - Gemfile.lock
  - README.md
  - LAUNCH_GUIDE.md

# Include specific files
include:
  - phase1-traditional/
  - phase2-modern/
  - phase3-ai-driven/
  - assets/
  - _config.yml

# SEO settings
seo:
  name: "Data Engineering Journey"
  description: "Complete hands-on course for engineering graduates: Traditional Data → Modern Engineering → AI-Driven Systems using GitHub Codespaces, Azure, and AI tools."
  keywords: "data engineering, machine learning, AI, vector database, knowledge graphs, MLOps, Azure, education, hands-on, interactive"

# Analytics (optional)
# google_analytics: "G-XXXXXXXXXX"

# Custom variables
course_features:
  - "Interactive demonstrations"
  - "GitHub Codespaces ready"
  - "Azure integration"
  - "AI-powered learning"
  - "Hands-on projects"
  - "Progressive complexity"

technologies:
  phase1:
    - "SQL"
    - "Python"
    - "Pandas"
    - "Chart.js"
    - "Power BI concepts"
  phase2:
    - "Azure"
    - "Docker"
    - "MLOps"
    - "Streaming analytics"
    - "Cloud architecture"
  phase3:
    - "Vector databases"
    - "Neo4j"
    - "OpenAI"
    - "LangChain"
    - "AI agents"

# Navigation
navigation:
  - name: "Overview"
    url: "#overview"
  - name: "Phases"
    url: "#phases"
  - name: "Features"
    url: "#features"
  - name: "Launch"
    url: "#launch"

# Course phases metadata
phase_metadata:
  phase1:
    title: "Traditional Data Engineering"
    duration: "Weeks 1-4"
    icon: "🏛️"
    description: "Master the fundamentals of data systems, SQL databases, and business intelligence"
    path: "phase1-traditional/html-dashboard/index.html"
  phase2:
    title: "Modern Data Engineering"
    duration: "Weeks 5-8"
    icon: "☁️"
    description: "Build cloud-native data architectures, MLOps pipelines, and real-time systems"
    path: "phase2-modern/mlops-pipeline/index.html"
  phase3:
    title: "AI-Driven Data Systems"
    duration: "Weeks 9-12"
    icon: "🤖"
    description: "Create intelligent data systems with vector databases, knowledge graphs, and AI agents"
    path: "phase3-ai-driven/vector-search/index.html"