Data Collection and Integration with Python and SQL

Raw data is rarely ready for analysis, often scattered across databases, websites, and external APIs. Knowing how to efficiently gather and unify this information is the foundational first step of any successful data project. This text-based course teaches you how to build robust pipelines that collect data from diverse sources and integrate them into clean, structured datasets. You will transition from manual data copying to writing automated Python scripts and SQL queries that handle real-world data challenges with confidence. What you'll learn: - Understand the foundational principles of data pipelines, schemas, and common formats like JSON, CSV, and XML. - Query relational databases using SQL to extract and filter the exact datasets you need. - Scrape web pages ethically using Beautiful Soup to extract unstructured online information. - Connect to modern web APIs to programmatically retrieve real-time data using secure authentication. - Merge and transform mismatched datasets using Pandas to create unified, clean data structures. - Validate incoming data quality using modern Python type hints and structured validation techniques. The course starts with fundamental concepts of data structures and storage, then guides you step-by-step through database querying, web scraping, API consumption, and data merging techniques. You will read clear explanations, study practical code snippets, and complete written exercises to reinforce your skills. Designed for absolute beginners to data engineering or analysis, this program requires only a basic familiarity with Python. Start building your first automated data pipelines today.