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Reading Data
Ria Cheruvu
Ria Cheruvu
In this course, you'll learn how to read data from various sources, like surveys, sensors, and machines, and how to use Python tools to clean, aggregate, and visualize it. You'll also explore the value of data for different use cases and industries.
Read more
In this course, you'll learn how to read data from various sources, like surveys, sensors, and machines, and how to use Python tools to clean, aggregate, and visualize it. You'll also explore the value of data for different use cases and industries.
Read more
In this course, you'll learn how to read data from various sources, like surveys, sensors, and machines, and how to use Python tools to clean, aggregate, and visualize it. You'll also explore the value of data for different use cases and industries.
Data is everywhere, but how can you make sense of it? In this course, Reading Data, you’ll gain the fundamental ability to identify and read data across a variety of sources, performing the first steps for clean and efficient data analysis.
First, you’ll explore the types of real-world data and the value they bring to different use cases, enabling you to determine what kind of data can best fit your use case.
Next, you’ll discover common data sources used in different industries (e.g.: surveys, sensor data, machine-generated data), their strengths and weaknesses, and their implementation using pandas with Python.
Then, you’ll implement data aggregations with sqlite3 in Python, allowing you to group and generate summary statistics and trends across multiple data points - a key aspect of data analysis.
Finally, you’ll learn how to understand and create impactful visualizations out of data to communicate insights from it.
When you’re finished with this course, you’ll have the skills and knowledge of reading data needed to mine different types of data from a variety of sources and maximize its value through aggregations and visualization, regardless of your use case.
Register for this course and see more details by visiting:
OpenCourser.com/course/j3cbu7/reading
What's inside
Syllabus
Course Overview
Identify and Determine Data Types
Identify Data Sources
Define, Apply, and Visualize Aggregations
Read more
Syllabus
Course Overview
Identify and Determine Data Types
Identify Data Sources
Define, Apply, and Visualize Aggregations
Read more
Craft Compelling Visuals and Insights from Data
Conclusion
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Examines a variety of data sources, such as surveys, sensors, and machines
Focuses on cleaning, aggregating, and visualizing data
Emphasizes the use of Python tools for data analysis
Suitable for individuals working with data in different industries
Covers the use of sqlite3 for data aggregations
Provides guidance on creating compelling data visualizations
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Activities
Coming soon
We're preparing activities for
Reading Data.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Reading Data will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts collect, clean, and interpret data to help businesses make informed decisions. They use statistical techniques and software to analyze data and identify trends and patterns. This course can help you develop the skills needed to be a successful Data Analyst, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
Data Scientist
Data Scientist
Data Scientists use their knowledge of mathematics, statistics, and computer science to solve complex problems. They develop and implement data-driven solutions to improve business outcomes. This course can help you build a foundation in data science by teaching you how to read, clean, and aggregate data, as well as how to create visualizations to communicate insights.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers develop and implement machine learning models to automate tasks and improve business outcomes. They use their knowledge of data science, machine learning algorithms, and software to build and deploy models that can learn from data and make predictions. This course can help you develop the skills needed to be a successful Machine Learning Engineer, including how to read and clean data, and how to create visualizations to communicate insights.
Data Engineer
Data Engineer
Data Engineers design, build, and maintain data infrastructure to support data analysis and machine learning. They use their knowledge of data management, software engineering, and cloud computing to build systems that can store, process, and analyze large amounts of data. This course can help you develop the skills needed to be a successful Data Engineer, including how to read and clean data, and how to create visualizations to communicate insights.
Business Analyst
Business Analyst
Business Analysts use data to help businesses understand their customers, make better decisions, and improve their operations. They use their knowledge of business, data analysis, and software to gather, analyze, and interpret data to identify trends and patterns. This course can help you develop the skills needed to be a successful Business Analyst, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to provide insights into complex problems. They use their knowledge of statistics, mathematics, and software to develop and implement statistical models to analyze data and identify trends and patterns. This course can help you develop the skills needed to be a successful Statistician, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
Data Visualization Analyst
Data Visualization Analyst
Data Visualization Analysts create visual representations of data to help businesses understand their data and make better decisions. They use their knowledge of data visualization techniques and software to create charts, graphs, and other visuals that can communicate insights from data. This course can help you develop the skills needed to be a successful Data Visualization Analyst, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
Market Researcher
Market Researcher
Market Researchers collect, analyze, and interpret data to understand consumer behavior and trends. They use their knowledge of market research techniques and software to conduct surveys, focus groups, and other research studies to gather data about consumers. This course can help you develop the skills needed to be a successful Market Researcher, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to help businesses improve their operations. They use their knowledge of mathematics, statistics, and software to develop and implement mathematical models to optimize business processes. This course can help you develop the skills needed to be a successful Operations Research Analyst, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
User Experience Researcher
User Experience Researcher
User Experience Researchers study how users interact with products and services to improve the user experience. They use their knowledge of human-computer interaction, research methods, and software to conduct user research studies to gather data about how users interact with products and services. This course can help you develop the skills needed to be a successful User Experience Researcher, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
Product Manager
Product Manager
Product Managers are responsible for the development and launch of new products. They use their knowledge of market research, product development, and business strategy to define the product vision, roadmap, and launch plan. This course can help you develop the skills needed to be a successful Product Manager, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
Financial Analyst
Financial Analyst
Financial Analysts use data to analyze the financial performance of companies and make investment recommendations. They use their knowledge of finance, accounting, and software to analyze financial data and develop financial models to predict future performance. This course can help you develop the skills needed to be a successful Financial Analyst, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
Management Consultant
Management Consultant
Management Consultants help businesses improve their performance. They use their knowledge of business strategy, operations management, and data analysis to identify areas for improvement and develop and implement solutions. This course can help you develop the skills needed to be a successful Management Consultant, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
Data Journalist
Data Journalist
Data Journalists use data to tell stories and inform the public. They use their knowledge of journalism, data analysis, and software to gather data, analyze data, and create visualizations to communicate insights to the public. This course can help you develop the skills needed to be a successful Data Journalist, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
Quantitative Researcher
Quantitative Researcher
Quantitative Researchers use data to analyze financial markets and make investment decisions. They use their knowledge of mathematics, statistics, and software to develop and implement quantitative models to analyze financial data and predict future performance. This course can help you develop the skills needed to be a successful Quantitative Researcher, including how to read data from different sources, clean and aggregate data, and create visualizations to communicate insights.
For more career information including salaries, visit:
OpenCourser.com/course/j3cbu7/reading
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
Reading Data.
Provides a comprehensive overview of data analysis with Python, covering topics such as data cleaning, data manipulation, and data visualization.
Provides a comprehensive overview of data science from scratch, covering topics such as data cleaning, data manipulation, data visualization, and machine learning.
Provides a comprehensive overview of Python for data analysis, covering topics such as data cleaning, data manipulation, and data visualization.
Provides a comprehensive overview of deep learning with Python, covering topics such as convolutional neural networks, recurrent neural networks, and deep learning models.
Provides a practical guide to data science with Python, covering topics such as data mining, machine learning, and deep learning.
Provides a practical guide to machine learning with Python, covering topics such as supervised learning, unsupervised learning, and deep learning.
Provides a practical guide to machine learning with Python, covering a wide range of topics from data preprocessing to model evaluation.
Save
Provides a comprehensive overview of data visualization for beginners, covering topics such as data exploration, data visualization techniques, and interactive visualization.
Provides a comprehensive overview of data visualization with Python, covering topics such as data exploration, data visualization techniques, and interactive visualization.
Provides a comprehensive overview of data science concepts and techniques, making it a valuable resource for those who want to learn more about the field.
Provides a comprehensive overview of data science for beginners, covering topics such as data cleaning, data manipulation, data visualization, and machine learning.
Provides a comprehensive overview of machine learning for beginners, covering topics such as supervised learning, unsupervised learning, and deep learning.
Provides a practical guide to automating tasks with Python, covering topics such as web scraping, data analysis, and data visualization.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/j3cbu7/reading
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Time
134 hours
Level
Introductory
Via
Pluralsight
Instructor
Ria Cheruvu
Language
English
Good to know
Examines a variety of data sources, such as surveys, sensors, and machines
Focuses on cleaning, aggregating, and visualizing data
Emphasizes the use of Python tools for data analysis
Suitable for individuals working with data in different industries
Covers the use of sqlite3 for data aggregations
Provides guidance on creating compelling data visualizations
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