Coursera MOOC / Non-credit 0

Data I/O and Preprocessing with Python and SQL

Name: Data I/O and Preprocessing with Python and SQL
Price: 49 USD
Availability: InStock

About this course

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.

75/100

CourseAsk score

What the provider tells you: 39/45
Who stands behind it: 20/35
How complete the listing is: 16/20

Scores how much the provider publishes and who stands behind it — not how well it is taught.

What you'll learn

extract data from webpages using Pandas and Beautiful Soup
handle unstructured text and apply ethical web scraping practices
access real-time data through APIs and parse JSON files
clean numerical data using normalization and binning techniques
manage authentication with API keys
query and join tables using SQL

Course objectives

to transform raw data into analysis-ready formats
to understand when to use SQL versus Python for preprocessing tasks

Data Analysis #python #pandas #data analysis #data cleaning #json #sql #data extraction #normalization #data preprocessing #api #binning #web scraping #beautiful soup

$49.00

Price shown by Coursera — confirm on their site.

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