Data Science Fundamentals: Sourcing and Wrangling Clean Data

In the real world, data is rarely clean, organized, or ready for analysis. To succeed in data science, you must know how to find, extract, and clean raw information from a variety of online sources. This text-only course teaches you the essential skills needed to gather and prepare your own datasets from scratch. By reading through clear explanations and studying practical code examples, you will transition from a beginner to a confident data gatherer. You will understand how to interact with web APIs, extract unstructured data from websites, and clean up messy datasets so they are ready for analysis. What you'll learn: - Learn the fundamental concepts of the data science lifecycle and data sourcing. - Understand how to make structured web requests to retrieve data from APIs. - Practice web scraping techniques to extract valuable information from HTML pages. - Apply data wrangling methods to clean, format, and structure messy datasets. - Merge and integrate diverse data sources into a single, cohesive dataset. - Utilize modern dataframe patterns to handle missing values and ensure data quality. This course begins with foundational definitions and key terminology before guiding you step-by-step through the mechanics of web requests, scraping, and data cleaning. It is designed entirely for beginners, requiring no prior background in data science or programming. Start building your data sourcing skills today with this comprehensive written guide.