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David Dalsveen

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.

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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

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What's inside

Syllabus

Project
In this 6-8 hour project, you'll use Python to perform Web Scraping on a Job Posting Site using Python and upload your results to your Coursera profile to showcase to potential employers.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Provides practical web scraping experience, which is a highly relevant skill in data science and data analysis
Empowers students to enhance their data extraction capabilities, a valuable asset in the job market
Suited for individuals seeking to develop their Python skills for data analysis and web scraping
Requires proficiency in Python programming, data cleaning, and web scraping techniques, catering to learners with a technical background
Provides an opportunity to showcase job scraping capabilities, demonstrating practical skills to potential employers

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Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Scrape and analyze data analyst job requirements with Python with these activities:
Review Python Basics
Refresh your understanding of Python basics, such as data types, loops, and functions, to strengthen your foundation for web scraping tasks.
Browse courses on Python
Show steps
  • Review Python documentation or tutorials
  • Practice writing Python code
Gather Resources on Web Scraping
Compile a list of useful resources on web scraping, including tutorials, articles, and tools, to enhance your learning experience.
Browse courses on Web Scraping
Show steps
  • Search for web scraping resources
  • Organize the resources in a document or spreadsheet
Join a Study Group for Web Scraping
Participate in a study group to discuss web scraping techniques, share knowledge, and get feedback on your progress.
Browse courses on Web Scraping
Show steps
  • Find a study group
  • Attend study group meetings
Six other activities
Expand to see all activities and additional details
Show all nine activities
Job Postings Collection
Create a collection of job postings from multiple sources to provide a comprehensive reference for your future job search.
Browse courses on Job Postings
Show steps
  • Identify relevant job boards and websites
  • Use web scraping techniques to extract job postings
  • Organize and filter the job postings based on criteria
  • Compile the job postings into a database or spreadsheet
  • Share your collection with others or use it for personal reference
Practice Web Scraping with BeautifulSoup
Practice using BeautifulSoup to extract data from web pages, reinforcing your understanding of web scraping techniques.
Browse courses on Web Scraping
Show steps
  • Install BeautifulSoup
  • Find a web page to scrape
  • Write a Python script to extract data from the web page
Web Scraping Data Visualization
Practice web scraping techniques to extract job postings and visualize the data, which will reinforce your understanding of Python's web scraping capabilities.
Browse courses on Web Scraping
Show steps
  • Gather target website URLs
  • Extract job posting data using BeautifulSoup
  • Clean and pre-process the extracted data
  • Visualize the data using a library like matplotlib or seaborn
  • Analyze and interpret the visualizations
Learn about Regular Expressions for Data Cleaning
Follow a guided tutorial to learn how to use regular expressions for cleaning and processing web scraped data, enhancing your data analysis skills.
Browse courses on Regular Expressions
Show steps
  • Find a tutorial on regular expressions
  • Follow the tutorial and practice using regular expressions
Python Web Scraping Project
Develop a Python-based web scraping project to demonstrate your skills and showcase your understanding of the course concepts.
Browse courses on Data Extraction
Show steps
  • Define the scope and objectives of your project
  • Identify and gather data sources
  • Write a Python script to extract the data
  • Clean and process the extracted data
  • Generate insights or build a data visualization
Develop a Web Scraping Application
Build a web scraping application that automates the extraction of data from multiple job posting sites, solidifying your understanding of web scraping and data analysis principles.
Browse courses on Web Scraping
Show steps
  • Design the application
  • Implement the web scraping functionality
  • Create a user interface for the application

Career center

Learners who complete Scrape and analyze data analyst job requirements with Python will develop knowledge and skills that may be useful to these careers:
Data Analyst
A Data Analyst is responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course can help you develop the skills needed to succeed in this role by providing you with hands-on experience in web scraping, data cleaning, and data visualization.
Data Scientist
A Data Scientist is responsible for developing and implementing data-driven solutions to business problems. This course can help you develop the skills needed to succeed in this role by providing you with hands-on experience in web scraping, data cleaning, and data visualization.
Market Researcher
A Market Researcher is responsible for collecting and analyzing data to understand market trends and consumer behavior. This course can help you develop the skills needed to succeed in this role by providing you with hands-on experience in web scraping, data cleaning, and data visualization.
Business Analyst
A Business Analyst is responsible for analyzing business processes and identifying areas for improvement. This course can help you develop the skills needed to succeed in this role by providing you with hands-on experience in web scraping, data cleaning, and data visualization.
Financial Analyst
A Financial Analyst is responsible for analyzing financial data to make investment recommendations. This course can help you develop the skills needed to succeed in this role by providing you with hands-on experience in web scraping, data cleaning, and data visualization.
Web Developer
A Web Developer is responsible for designing and developing websites. This course can help you develop the skills needed to succeed in this role by providing you with hands-on experience in web scraping, data cleaning, and data visualization.
Statistician
A Statistician is responsible for collecting, analyzing, and interpreting data. This course can help you develop the skills needed to succeed in this role by providing you with hands-on experience in web scraping, data cleaning, and data visualization.
Operations Research Analyst
An Operations Research Analyst is responsible for using data to develop and implement solutions to improve business operations. This course can help you develop the skills needed to succeed in this role by providing you with hands-on experience in web scraping, data cleaning, and data visualization.
Data Engineer
A Data Engineer is responsible for designing and building data pipelines. This course can help you develop the skills needed to succeed in this role by providing you with hands-on experience in web scraping, data cleaning, and data visualization.
Systems Analyst
A Systems Analyst is responsible for analyzing and designing business systems. This course may be useful for this role by providing some hands-on experience in web scraping and data cleaning.
Data Architect
A Data Architect is responsible for designing and managing data systems. This course may be useful for this role by providing some hands-on experience in data cleaning and data visualization.
Software Engineer
A Software Engineer is responsible for designing, developing, and testing software. This course may be useful for this role by providing some hands-on experience in data cleaning and data visualization.
Database Administrator
A Database Administrator is responsible for managing and maintaining databases. This course may be useful for this role by providing some hands-on experience in web scraping and data cleaning.
Computer Scientist
A Computer Scientist is responsible for researching and developing new computer technologies. This course may be useful for this role by providing some hands-on experience in web scraping and data cleaning.
Information Technology Manager
An Information Technology Manager is responsible for planning and managing the implementation of information technology systems. This course may be useful for this role by providing some hands-on experience in web scraping and data cleaning.

Reading list

We've selected seven books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Scrape and analyze data analyst job requirements with Python.
Provides a comprehensive guide to web scraping with Python, covering various techniques and tools for extracting data from websites. It is particularly useful for those seeking practical knowledge in web scraping for data analysis.
Delves into data manipulation techniques in Python, focusing on real-world applications for data analysts. It complements the course's emphasis on web scraping by providing a solid foundation in data cleaning, wrangling, and analysis.
This beginner-friendly book introduces programming concepts and Python basics. It covers web scraping techniques among other practical applications, providing a foundation for those new to Python or programming in general.
This online documentation serves as a valuable reference for BeautifulSoup, the Python library used for web scraping in the course. It provides detailed explanations, examples, and API references for effective use of the library.
This comprehensive handbook covers a wide range of data science topics, including web scraping. It provides valuable insights into data analysis, machine learning, and visualization techniques, complementing the course's focus on web scraping and data analysis.
Serves as a comprehensive reference for Python, providing detailed explanations of the language's syntax, semantics, and built-in functions. It offers a valuable resource for those seeking to expand their Python knowledge and improve their coding skills.

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