Introduction to Data Engineering
Chapter 1: What is Data Engineering?
Defining Data Engineering
The Role of a Data Engineer
Data Engineering vs Data Science vs Data Analysis
Common Data Engineering Tasks
Why Data Engineering Matters for AI
Chapter 2: Foundational Concepts
Data Sources and Collection Methods
Introduction to Databases
Data Warehouses Explained
Introduction to APIs for Data Retrieval
Hands-on Practical: Identifying Data Types
Chapter 3: Building Your First Data Pipeline
Data Extraction Techniques
Basic Data Transformation Operations
Loading Data into Storage
Simple Pipeline Orchestration Concepts
Practice: Sketching a Basic Pipeline
Chapter 4: Data Storage Fundamentals
Choosing the Right Data Storage
Working with Relational Databases (SQL Basics)
Introduction to NoSQL Databases
Understanding File Storage Systems
Practice: Setting up a Simple Database Table
Chapter 5: Introduction to Data Processing
Batch Processing Explained
Stream Processing Explained
Processing Frameworks Overview
Understanding Compute Resources
Data Validation Techniques
Practice: Simple Data Cleaning Script
Chapter 6: Essential Tools for Data Engineers
Introduction to SQL for Data Manipulation
Version Control with Git for Code
Command-Line Interface (CLI) Basics
Overview of Cloud Platforms
Introduction to Workflow Schedulers
Practice: Basic Git Commands
Chapter 7: Next Steps in Data Engineering
Areas for Further Learning
Building a Portfolio Project Idea
Contributing to Open Source
Keeping Up with New Tools