O`Reilly – Business Data Analytics With Python-iLLiTERATE
English | Tutorial | Size: 1.61 GB
Many business analysts believe that the only way to analyze data is by creating simple charts and estimating simple linear models. However, to truly extract the key information buried inside your business data-information that is important for making sound and reasonable business decisions-you need to perform sophisticated, high-powered analyses.
In this three-hour hands-on course, expert Walter Paczkowski walks you through data visualization and statistical methods implemented in Python for analyzing business data, whether sales, personnel, logistics, marketing, or financial. You’ll explore the nature of business data, the application and interpretation of statistical and machine learning methods for gaining insight into your business, and how to present conclusions in tabular and graphical formats. By the end of the course, you’ll be able to use Python to interactively visualize data, estimate predictive models, and distribute reports from Jupyter notebooks.
What you’ll learn and how you can apply it
By the end of this course, you’ll understand:
How to use Jupyter notebooks to manage an analytical assignment
How to use several Python packages for business analysis, including pandas for data manipulation; StatsModels, SciPy, and scikit-learn for modeling; and Seaborn for visualization
How to import different data formats (CSV, Excel, etc.) into pandas
How to divide data into training and test datasets for validation
How to visualize business data
How to estimate and interpret statistical models, such as OLS and logistic regression
How to cross-validate model estimations
How to export Jupyter notebooks to the HTML and PDF formats for sharing
And you’ll be able to:
Take a new business dataset and analyze it for key insights using the Python packages
Visualize business data for key insights, such as relationships, trends, patterns, and anomalies
You’re a business analyst responsible for conducting, analyzing, and interpreting data for key business decisions, and you want to learn how to use Python and its main packages.
You want to expand your knowledge of and experience with toolsets for analytical methods, such as machine learning, and software so you can provide the best insights to your clients and advance your career.
Prerequisites
A basic understanding of statistics and regression analysis
The ability to interpret basic data visualization tools such as box plots, histograms, and scatter plots
Experience working with business datasets
Familiarity with business problems and functional areas such as marketing, sales, and finance
Recommended preparation:
Read chapters 2 and 5-10 in Python for Data Analysis (book)
Read Introduction to Machine Learning with Python (book)
PEARSON OOWNS MAANY EDU BRAANDS INKLUDINNG
ADDISON-WESLEY PEACHPIT PRENTICE-HALL ECOLLEGE
AND MAANY MORE!
WEE ASUMME NO LIIABILLITY FUR A WROONG SPELING
COZ WEE ARRE A NON (iL)LiTERATE GRUP!!
TANNKS TU THE LITERATE ASKII FRIIEND!!
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