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Introduction to Data
Brad Batesole,
Anke Audenaert,
Mat Leonard,
Dana Sheahen,
and
Josh Bernhard
Brad Batesole,
Anke Audenaert,
Mat Leonard,
Dana Sheahen,
and
Josh Bernhard
Register for this course and see more details by visiting:
OpenCourser.com/course/b94gz2/introduction
What's inside
Syllabus
In this lesson, you will learn about data types, measures of center, and the basics of statistical notation.
In this lesson, you will learn about measures of spread, shape, and outliers as associated with quantitative data. You will also get a first look at inferential statistics.
Read more
Syllabus
In this lesson, you will learn about data types, measures of center, and the basics of statistical notation.
In this lesson, you will learn about measures of spread, shape, and outliers as associated with quantitative data. You will also get a first look at inferential statistics.
Read more
In this lesson, you will learn about the basic functionality for spreadsheet software, use cell referencing and menu shortcuts.
Project: Working with Data
In this lesson, you will learn basic spreadsheet function: sort and filter data, use text and math functions, split columns and remove duplicates.
In this lesson, you will learn how to summarize data with aggregation and conditional functions. You will learn how to use pivot tables and lookup functions.
In this lesson you will build data visualizations for quantitative and categorical data; create pie, bar, line, scatter, histogram, and boxplot charts, and build professional presentations.
Project: Analyze Survey Data
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Builds a strong foundation for beginners by introducing basic spreadsheet fundamentals
Covers basic spreadsheet functionality and features, which can be useful in various settings
Introduces data analysis concepts and techniques, which are valuable for making informed decisions
Provides hands-on practice through projects, enabling learners to apply their knowledge and gain proficiency
Taught by experienced instructors, indicating the course's credibility and quality
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Activities
Coming soon
We're preparing activities for
Introduction to Data.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Introduction to Data will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
A professional who extracts insights and patterns from data using scientific methods, often involving data mining, machine learning, and statistical analysis. This course can help you understand data storage, types, and common data tools. You will also learn to apply statistical methods to gain insights from complex data.
Statistician
Statistician
A Statistician designs, conducts, and interprets statistical studies to collect and analyze data. They use their findings to make informed decisions and solve problems. This course will teach you the basics of statistical notation and how to use statistical methods to draw conclusions from data.
Database Administrator
Database Administrator
A Database Administrator is responsible for the design, implementation, and maintenance of corporate databases. This course will help you understand data storage, types, and common data tools.
Data Analyst
Data Analyst
A professional who collects, analyzes, and interprets data to help organizations make informed decisions. This course will teach you the basics of data analysis, including data cleaning, data preparation, and data visualization.
Business Analyst
Business Analyst
A professional who analyzes business processes and systems to identify areas for improvement. This course will teach you the basics of data analysis, including data cleaning, data preparation, and data visualization.
Market Researcher
Market Researcher
A professional who conducts research to gather information about target markets, customer preferences, and industry trends. This course will teach you the basics of data analysis, including data cleaning, data preparation, and data visualization.
Financial Analyst
Financial Analyst
A professional who analyzes financial data to make investment recommendations and assess the financial health of companies and organizations. This course will teach you the basics of data analysis, including data cleaning, data preparation, and data visualization.
Operations Research Analyst
Operations Research Analyst
A professional who uses mathematical and analytical methods to solve complex business problems. This course will teach you the basics of data analysis, including data cleaning, data preparation, and data visualization.
Management Consultant
Management Consultant
A professional who helps organizations improve their performance by providing advice on strategy, operations, and technology. This course will teach you the basics of data analysis, including data cleaning, data preparation, and data visualization.
Software Engineer
Software Engineer
A professional who designs, develops, and maintains software applications. This course will teach you the basics of data structures and algorithms, which are essential for software development.
Computer Scientist
Computer Scientist
A professional who studies the theory and application of computer science. This course will teach you the basics of data structures and algorithms, which are essential for computer science.
Data Engineer
Data Engineer
A professional who designs, builds, and maintains data pipelines and infrastructure. This course will teach you the basics of data storage, types, and common data tools.
Information Architect
Information Architect
A professional who designs and organizes information systems to meet the needs of users. This course will teach you the basics of data storage, types, and common data tools.
Technical Writer
Technical Writer
A professional who writes and edits technical documentation, such as user manuals, training materials, and technical reports. This course may help you understand the basics of data analysis, which can be helpful for writing about technical topics.
Librarian
Librarian
A professional who helps people find and access information. This course may help you understand the basics of data storage and organization, which can be helpful for working with library resources.
For more career information including salaries, visit:
OpenCourser.com/course/b94gz2/introduction
Reading list
We've selected 12 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
Introduction to Data.
Save
Deep Learning comprehensive introduction to deep learning, and is especially useful for learning more about the different types of deep learning architectures and how to build deep learning models.
Deep Learning with Python provides a comprehensive introduction to deep learning with Python, and is especially useful for learning more about the different types of deep learning architectures and how to implement them in Python.
The Art of Data Analysis provides a practical guide to data analysis, and is especially useful for learning more about how to approach and solve data analysis problems.
Save
Data Mining: Practical Machine Learning Tools and Techniques comprehensive introduction to data mining techniques, and is especially useful for learning more about how to use data mining techniques to solve real-world problems.
Introduction to Data Science provides a comprehensive overview of data science, and is especially useful for learning more about the different aspects of data science, including data collection, data preprocessing, data analysis, and data visualization.
Data Science for Business provides a practical guide to data science for business professionals, and is especially useful for learning more about how to use data science to solve business problems.
The Data Science Design Manual provides a practical guide to data science project design, and is especially useful for learning more about how to design and implement successful data science projects.
Save
Data Visualization: A Practical Introduction great resource for learning more about how to create effective data visualizations. It is especially useful for learning more about the different types of data visualizations and how to choose the right visualization for your data.
Data Science from Scratch provides a hands-on introduction to data science, and is especially useful for learning more about how to use Python for data science.
Data Analysis Using Excel great resource for learning more about how to use spreadsheet software for data analysis. It is especially useful for learning more about the functions and features of Microsoft Excel.
The Statistical Sleuth comprehensive introduction to data analysis techniques, and is especially useful for learning more about inferential statistics. It is more valuable as a current reference than it is as background reading.
Introduction to Statistical Thinking provides a great overview of basic statistical concepts, and is helpful for solidifying the material you learn from this course. It is more valuable as background reading than it current reference.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/b94gz2/introduction
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Time
24480 hours
Level
Introductory
Via
Udacity
Instructors
Brad Batesole
Anke Audenaert
Mat Leonard
Dana Sheahen
Josh Bernhard
Language
English
Good to know
Builds a strong foundation for beginners by introducing basic spreadsheet fundamentals
Covers basic spreadsheet functionality and features, which can be useful in various settings
Introduces data analysis concepts and techniques, which are valuable for making informed decisions
Provides hands-on practice through projects, enabling learners to apply their knowledge and gain proficiency
Taught by experienced instructors, indicating the course's credibility and quality
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