4 Data Analyst Career Paths: Your Guide to Leveling Up
Getting a job as a data analyst can open up a variety of exciting career paths, including data science, management, consulting, or specialization.
February 14, 2025
Article
7,687 already enrolled
Recommended experience
Intermediate level
Python, CSV, Visualization, BeautifulSoup, Git, Jupyter Notebook
Recommended experience
Intermediate level
Python, CSV, Visualization, BeautifulSoup, Git, Jupyter Notebook
Increase the efficiency of job vacancy sourcing
Improve the quality of job vacancy sourcing
Gain a competitive advantage
Add to your Coursera profile
Use a Coursera Lab, a pre-configured in-browser cloud workspace (only available on desktop)
In this project, you’ll help a recruitment agency improve its job vacancy sourcing by using Python’s web-scraping capabilities to extract job postings from multiple sites.
This task will require you to write a Python script to extract job posting data from the source site and save it to a comma separated values (CSV) file. Your work will help the agency provide clients with with relevant job openings more quickly, giving them a competitive advantage over other applicants. There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers. ROLE: Data Analyst SKILLS: Python PREREQUISITES: variables, data types, loops, functions, and file input/output in Python web scraping techniques data cleaning, preprocessing, and visualization techniques BeautifulSoup, Git, Jupyter Notebook
This project requires you to independently complete the following steps:
Import required libraries
Generate a URL with a function
Extract the Job Data from a single job posting card
Define the main function
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Projects give you real-world challenges to solve with industry tools, and produce work samples that you can add to your Coursera Skills Profile to help you stand out to employers.
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