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    Complete Statistics BootCamp: Hands-On with Python

    Posted By: BlackDove
    Complete Statistics BootCamp: Hands-On with Python

    Complete Statistics BootCamp: Hands-On with Python
    Genre: eLearning | MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
    Language: English | Size: 2.53 GB | Duration: 8h 18m

    Learn how to apply probability and statistics to real data science and business applications using an hands-on approach

    What you'll learn
    Understand the fundamentals of statistics
    Visualizing data, including bar graphs, , histograms, and scatter plots
    Analyzing data, including mean, median, and mode, plus range and IQR and box-and-whisker plots
    Data distributions, including mean, variance, and standard deviation, and normal distributions and z-scores
    Probability, independent and dependent events and Bayes' theorem
    Sampling, including types of studies, bias, and sampling distribution of the sample mean or sample proportion, and confidence intervals
    Hypothesis testing, including inferential statistics, significance levels, type I and II errors, test statistics, and p-values
    Regression, including scatterplots, correlation coefficient, the residual, coefficient of determination, RMSE,
    Extensive Case Studies that will help you reinforce everything you’ve learned
    Build hands-on statistical toolset from scratch using Python

    Description
    Welcome to Complete Statistics BootCamp: Hands-On with Python

    This course will cover all the core statistics knowledge required to succeed in data science, machine learning, or business analytics.

    This practical course will go over hands-on implementation of statistics knowledge on real-world problems using Python programming language.

    We will start by talking briefly about the basics of tools we will be using in the course, such as visualization, Scipy Stack, Numpy, etc.

    Then to give you a real-world experience of applying this toolset, we will jump right into three concrete real-world case studies, which deal with scientific testing, linear and logistic regression. This front-loading will allow the students to "play the whole game" and get an overall experience of real-world settings.

    In the next module, we will systematically build our statistical knowledge and toolset from scratch, using only plain and simple Python code, which can easily be replicated in any programming language or environment. We will cover topics ranging from building function in linear algebra to building core statistical operations like central tendency, dispersion, correlation, creating distributions tools from scratch, and then finally building our hypothesis testing toolset.

    The sections are modular and organized by topic, so you can reference what you need and jump right in!

    Concepts covered will include:

    Measurements of Data

    Mean, Median, and Mode

    Variance and Standard Deviation

    Co-variance and Correlation

    Conditional Probability

    Bayes Theorem

    Binomial Distribution

    Normal Distribution

    Sampling

    Central Limit Theorem

    Hypothesis Testing

    T-Distribution Testing

    Regression Analysis

    ANOVA

    and much more!

    All of this content comes with a 30 day money back guarantee, so you can try out the course risk free!

    So what are you waiting for? Enroll today and we'll see you inside the course!

    Who this course is for:
    Current probability and statistics students, or students about to start probability and statistics who are looking to get ahead
    Business analysts
    People who want to start learning statistics
    People who want to learn the fundamentals of statistics
    People who want a career in Data Science
    Anybody who wants to get hands-on experience building stats