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Answering Interesting Questions with Data
Barbara Ericson
Barbara Ericson
There is a huge amount of raw data available on the internet with endless potential.
Read more
There is a huge amount of raw data available on the internet with endless potential.
Read more
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.
Register for this course and see more details by visiting:
OpenCourser.com/course/z6eq63/answering
What's inside
Syllabus
Week 1: HTML and Beautiful Soup
Week 2: XML, JSON, and APIs
Week 3: Databases and SQL
Read more
Syllabus
Week 1: HTML and Beautiful Soup
Week 2: XML, JSON, and APIs
Week 3: Databases and SQL
Read more
Week 4: More Databases and Visualizing Data
Good to know
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
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Answering Interesting Questions with Data.
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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 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.
Data Scientist
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.
Data Warehouse Engineer
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.
Data Architect
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.
Data Engineer
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.
Data Analyst
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.
Data Visualization Developer
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.
Operations Research Analyst
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.
Database Administrator
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.
Information Security Analyst
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.
Risk Analyst
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.
Quantitative Analyst
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.
Business Intelligence Analyst
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.
Web Developer
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.
Software Engineer
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.
For more career information including salaries, visit:
OpenCourser.com/course/z6eq63/answering
Reading list
We've selected 13 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
Answering Interesting Questions with Data.
Provides a comprehensive overview of data science using Python. It covers a wide range of topics, including data cleaning, data manipulation, data visualization, and machine learning. It valuable reference for data scientists of all levels.
Provides a comprehensive overview of statistical learning. It covers a wide range of topics, including statistical learning algorithms, statistical learning models, and statistical learning applications.
Is an excellent primer on data science and machine learning. It provides a broad overview of the field, including data mining, data analysis, and machine learning. It can also serve as a valuable reference.
Save
Provides a comprehensive overview of deep learning. It covers a wide range of topics, including deep learning architectures, deep learning algorithms, and deep learning applications.
Save
Provides a comprehensive overview of computer vision. It covers a wide range of topics, including computer vision algorithms, computer vision techniques, and computer vision applications.
Save
Provides a comprehensive overview of data visualization. It covers a wide range of topics, including data visualization principles, data visualization techniques, and data visualization tools.
Provides a comprehensive overview of reinforcement learning. It covers a wide range of topics, including reinforcement learning algorithms, reinforcement learning models, and reinforcement learning applications.
Provides a comprehensive overview of Bayesian reasoning and machine learning. It covers a wide range of topics, including Bayesian reasoning algorithms, Bayesian reasoning models, and Bayesian reasoning applications.
Provides a comprehensive overview of reinforcement learning and optimal control. It covers a wide range of topics, including reinforcement learning algorithms, optimal control algorithms, and reinforcement learning applications.
Provides a comprehensive overview of machine learning from a probabilistic perspective. It covers a wide range of topics, including probabilistic machine learning algorithms, probabilistic machine learning models, and probabilistic machine learning applications.
Provides a comprehensive overview of convex optimization. It covers a wide range of topics, including convex optimization algorithms, convex optimization models, and convex optimization applications.
Provides a comprehensive overview of information retrieval. It covers a wide range of topics, including information retrieval algorithms, information retrieval techniques, and information retrieval applications.
Provides a comprehensive overview of natural language processing. It covers a wide range of topics, including natural language processing techniques, natural language processing tools, and natural language processing applications.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/z6eq63/answering
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Level
Intermediate
Via
Coursera
Institution
University of Michigan
Instructor
Barbara Ericson
Language
English
This course belongs to a
collection
called
Creative Coding: Hands-On Python. It's comprised of four courses:
- The Power of Object-Oriented Programming
- Big Ideas in Programming: Expressing Yourself with Python
- Answering Interesting Questions with Data (viewing)
- Debugging: Hunting and Squashing Bugs
Good to know
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
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