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Most real-world data isn鈥檛 clean, it鈥檚 messy, incomplete, and spread across sources like websites, APIs, and databases. In this course, you鈥檒l learn how to collect that data, clean it, and prepare it for analysis using Python and SQL. You鈥檒l 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鈥檒l access real-time data through APIs, parse JSON files, and clean numerical data using techniques like normalization and binning. You鈥檒l also learn how to manage authentication with API keys and store them securely. Finally, you鈥檒l 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鈥檒l be able to turn raw, real-world data into reliable, analysis-ready inputs鈥攁 core skill for any data professional.