Answering Interesting Questions with Data from Coursera

There is a huge amount of raw data available on the internet with endless potential.

This four-week course from the University of Michigan will help you learn how to read data in different formats and write programs to scrape data from the internet.

Once you complete this course, you’ll be empowered with the ability to use data to answer high-level and interesting questions.

An essential component of data collection and analysis is the ability to store and manage the data effectively once you’ve retrieved it.

You’ll learn how to use SQL to manage data in relational databases in order to create linked datasets and gain insight into the relationships and meaning that can be derived from your data.

Data is a powerful tool, but its potential can only be unleashed once it is converted and represented as logical information. This process is referred to as data visualization, and it is key to understanding and analyzing data.

You’ll be taught to use charts, scatter plots, graphs, and other mediums in order to transform your data into valuable information that can be used to answer interesting questions.

This course is designed for learners who are interested in extending their Python knowledge, learning a textual programming language, or who would like to be able to communicate with programmers in a professional setting.

What's inside

Syllabus

Week 1: HTML and Beautiful Soup

Week 2: XML, JSON, and APIs

Week 3: Databases and SQL

Week 4: More Databases and Visualizing Data

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Develops the ability to use data to answer questions, manage data in databases, and transform data into visual information

Taught by instructors from the University of Michigan

Teaches foundational Python skills, including how to read data in different formats and write programs to scrape data from the internet

Focuses on the use of databases, SQL, and data visualization to analyze data in order to gain insight into relationships and meaning

Students who are interested in learning to communicate with programmers in a professional setting may benefit from this course

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 Answering Interesting Questions with Data with these activities:

Seek Mentorship from Industry Professionals

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Enhance your learning by seeking guidance from experienced data scientists or industry professionals who can provide valuable insights and support.

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Attend industry events and meetups to network with data professionals
Reach out to potential mentors via LinkedIn or email

Review: Web Data Extraction

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Refresh your understanding of methods and techniques for extracting data from HTML by reviewing Python library documentation and tutorials.

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Review documentation for the BeautifulSoup library
Read through the BeautifulSoup documentation and tutorials

Book Review: Data Science for Business

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Gain insights into the practical applications of data science in business by reading and reviewing a key text in the field.

View Data Science for Business: What You Need to... on Amazon

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Read the book and make notes on key concepts and examples
Summarize the main takeaways from the book in a written review

Four other activities

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Guided Tutorial: XML and JSON

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Enhance your understanding of XML and JSON data formats by following guided tutorials that demonstrate how to parse and manipulate these data structures in Python.

Browse courses on XML

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Find online tutorials for parsing XML and JSON in Python
Follow the tutorials step-by-step, practicing the techniques shown

Practice Drills: SQL

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Reinforce your SQL skills through dedicated practice drills that cover various data manipulation and querying techniques.

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Solve SQL practice problems from online resources
Create a set of sample data and practice writing queries against it

Contribute to Open Source Data Projects

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Engage with the broader data science community by contributing to open source data projects on platforms like GitHub, showcasing your skills and gaining valuable experience.

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Identify open source data projects aligned with your interests
Find a project that has a clear issue or feature request
Submit a pull request with your proposed contribution

Project: Data Visualization Dashboard

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Demonstrate your proficiency in data visualization by creating an interactive dashboard using Tableau or other data visualization tools to present insights from a given dataset.

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Gather and prepare a dataset relevant to the course topics
Design and create a data visualization dashboard using Tableau
Share and present your dashboard to classmates or a broader audience

Career center

Learners who complete Answering Interesting Questions with Data will develop knowledge and skills that may be useful to these careers:

Machine Learning Engineer

Machine Learning Engineers develop and deploy machine learning models to solve business problems. They work with Data Scientists to build models, and they develop the infrastructure to deploy and manage those models. This course would be helpful for Machine Learning Engineers because it teaches how to use Python and SQL to analyze data and build data pipelines. This knowledge would help Engineers to be more efficient in their work and to develop more accurate models.

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Data Scientist

Data Scientists combine the skills of Data Analysts and Machine Learning Engineers to develop predictive models and solve complex business problems. They use data to build algorithms and models that can be used to make predictions about the future. This course would be helpful for Data Scientists because it teaches how to use Python and SQL to analyze data and build data pipelines. This knowledge would help Scientists to be more efficient in their work and to develop more accurate models.

See salaries and explore the career path for Data Scientist

Data Warehouse Engineer

Data Warehouse Engineers design and build data warehouses. They work with Data Analysts and Business Intelligence professionals to gather requirements and design data warehouses that meet the needs of the business. This course would be helpful for Data Warehouse Engineers because it teaches how to use Python and SQL to analyze data and build data pipelines. This knowledge would help Engineers to be more efficient in their work and to develop more effective data warehouses.

See salaries and explore the career path for Data Warehouse Engineer

Data Architect

Data Architects design and build data architectures. They work with Data Analysts and Business Intelligence professionals to gather requirements and design data architectures that meet the needs of the business. This course would be helpful for Data Architects because it teaches how to use Python and SQL to analyze data and build data pipelines. This knowledge would help Architects to be more efficient in their work and to develop more effective data architectures.

See salaries and explore the career path for Data Architect

Data Engineer

Data Engineers build and maintain data pipelines. They work with Data Scientists and Machine Learning Engineers to develop data pipelines that provide data for models and algorithms. This course would be helpful for Data Engineers because it teaches how to use Python and SQL to analyze data and build data pipelines. This knowledge would help Engineers to be more efficient in their work and to develop more effective data pipelines.

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Data Analyst

Data Analysts use their skills to help businesses understand their data and make better decisions. They analyze data to identify trends and patterns, and they develop visualizations to present their findings. This course would be useful for Data Analysts because it teaches how to use Python and SQL to analyze data. This knowledge would help Analysts to be more efficient in their work and to gain insights from data that would not be possible to obtain manually.

See salaries and explore the career path for Data Analyst

Data Visualization Developer

Data Visualization Developers create visualizations that communicate data insights to users. They work with Data Analysts and Business Intelligence professionals to develop visualizations that are clear, concise, and informative. This course would be helpful for Data Visualization Developers because it teaches how to use Python and SQL to analyze data and build data pipelines. This knowledge would help Developers to be more efficient in their work and to develop more effective visualizations.

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Operations Research Analyst

Operations Research Analysts develop and use mathematical models to solve business problems. They work with businesses to identify and solve problems related to efficiency, productivity, and profitability. This course would be helpful for Operations Research Analysts because it teaches how to use Python and SQL to analyze data and build data pipelines. This knowledge would help Analysts to be more efficient in their work and to develop more effective models.

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Database Administrator

Database Administrators manage and maintain databases. They ensure that databases are available and performant, and they protect databases from security threats. This course would be useful for Database Administrators because it teaches how to use SQL to manage data in relational databases. This knowledge would help Administrators to be more efficient in their work and to ensure that databases are running smoothly.

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Information Security Analyst

Information Security Analysts protect computer systems and networks from security threats. They identify vulnerabilities in systems and develop security measures to mitigate those vulnerabilities. This course would be helpful for Information Security Analysts because it teaches how to use Python and SQL to analyze data and identify security threats. This knowledge would help Analysts to be more efficient in their work and to develop more effective security measures.

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Risk Analyst

Risk Analysts identify and assess risks to businesses. They work with businesses to develop and implement risk management strategies. This course would be helpful for Risk Analysts because it teaches how to use Python and SQL to analyze data and build data pipelines. This knowledge would help Analysts to be more efficient in their work and to identify and assess risks more effectively.

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Quantitative Analyst

Quantitative Analysts use mathematical and statistical models to analyze financial data. They work with investment banks and hedge funds to make investment decisions. This course would be helpful for Quantitative Analysts because it teaches how to use Python and SQL to analyze data and build data pipelines. This knowledge would help Analysts to be more efficient in their work and to develop more effective models.

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Business Intelligence Analyst

Business Intelligence Analysts use data to help businesses make better decisions. They analyze data to identify trends and patterns, and they develop visualizations to present their findings. This course would be useful for Business Intelligence Analysts because it teaches how to use Python and SQL to analyze data. This knowledge would help Analysts to be more efficient in their work and to gain insights from data that would not be possible to obtain manually.

See salaries and explore the career path for Business Intelligence Analyst

Web Developer

Web Developers are responsible for developing and maintaining websites. They create the code that makes a website work, and they ensure that the site is visually appealing and easy to navigate. This course would be helpful for Web Developers because it teaches how to read data in different formats and write programs to scrape data from the internet. This knowledge would help Developers to gather data for their websites and to create more dynamic and engaging web experiences.

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Software Engineer

Software Engineers design, develop, and maintain software systems. They work on a wide variety of projects, from enterprise applications to mobile apps. This course would be helpful for Software Engineers because it teaches how to read data in different formats and write programs to scrape data from the internet. This knowledge would help Engineers to gather data for their projects and to develop more dynamic and engaging software experiences.

See salaries and explore the career path for Software Engineer