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Scrape and analyze data analyst job requirements with Python

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

Coming soon We're preparing activities for Scrape and analyze data analyst job requirements with Python. These are activities you can do either before, during, or after a course.

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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