Data I/O and Preprocessing with Python and SQL

Most real-world data isn’t clean, it’s messy, incomplete, and spread across sources like websites, APIs, and databases. In this course, you’ll learn how to collect that data, clean it, and prepare it for analysis using Python and SQL. You’ll start by extracting data from webpages using tools like Pandas and Beautiful Soup, while also learning how to handle unstructured text and apply ethical scraping practices. Next, you’ll access real-time data through APIs, parse JSON files, and clean numerical data using techniques like normalization and binning. You’ll also learn how to manage authentication with API keys and store them securely. Finally, you’ll work with databases: Querying and joining tables using SQL, validating results, and understanding when to use SQL versus Python for different preprocessing tasks. By the end of the course, you’ll be able to turn raw, real-world data into reliable, analysis-ready inputs—a core skill for any data professional

• Handle real-world messy, unstructured data from multiple sources
• Extract data from websites, APIs, and databases
• Clean and prepare data using Python and SQL for analysis
• Utilize Pandas and Beautiful Soup for text data processing
• Apply cleaning techniques like normalization and binning
• Manage and secure API keys effectively

• No prior experience required