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Teach Yourself Data Analytics in 30 Days
Would you like to learn how to extract useful insights from all the data around you without having to take years' worth of courses? College data science programs teach many valuable skills, but sometimes all you need is some quick and direct tools. Welcome to Teach Yourself Data Analytics in 30 Days.
The book's curriculum is organized into eight data "stories." The stories are interesting on their own, but there's no doubt what they're really all about is Python data analytics. Each story/chapter contains all the information you would need to go out and get the raw data and then write the Python analytics code necessary to solve a specific problem. Once you've worked through the whole book, you'll have enough Python skills to solve a wide range of data problems on your own.
If you're motivated and have some time to invest, there's no reason you can't use those stories to teach yourself data analytics in 30 days. You'll find everything you need to build your own basic data analytics skills, including:
* Getting Python up and running on Jupyter Notebooks (or, if you prefer, JupyterLab)
* Finding and cleaning data sources
* Plotting your data
* Using Python functions
* Understanding results through domain knowledge and tools like regression lines
The book's curriculum is organized into eight data "stories." The stories are interesting on their own, but there's no doubt what they're really all about is Python data analytics. Each story/chapter contains all the information you would need to go out and get the raw data and then write the Python analytics code necessary to solve a specific problem. Once you've worked through the whole book, you'll have enough Python skills to solve a wide range of data problems on your own.
If you're motivated and have some time to invest, there's no reason you can't use those stories to teach yourself data analytics in 30 days. You'll find everything you need to build your own basic data analytics skills, including:
* Getting Python up and running on Jupyter Notebooks (or, if you prefer, JupyterLab)
* Finding and cleaning data sources
* Plotting your data
* Using Python functions
* Understanding results through domain knowledge and tools like regression lines
- GenresNonfiction
108 pages, Kindle Edition
Published April 30, 2021
7 people are currently reading
390 people want to read
About the author
David Clinton
11 books14 followersDavid Clinton is an AWS solutions architect and a Linux system administrator. He is the author of a dozen books and two dozen Pluralsight courses on AWS, Linux, IT security, and server virtualization.
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Displaying 1 of 1 review
May 20, 2021
Good book
This is very informative book.I think that anyone who wants to learn data analytics will like this book.I would recommend it
This is very informative book.I think that anyone who wants to learn data analytics will like this book.I would recommend it
Displaying 1 of 1 review