Become a Python Data Analyst

Become a Python Data Analyst

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This course introduces you to the main libraries of Python's Data Science stack. Taking an applied approach, it provides examples using real-world datasets to show you how to effectively use Python's tools to process, visualize and analyze data. It contains all you need to start analyzing data with Python and provides the foundation for more advanced topics like Predictive Analytics.
20171 temporada
Interés general
Interés general
20171 temporada
Reparto: Alvaro Fuentes
TODOS
Temporada 1
26 episodios

  • 1. The Course Overview

    1. The Course Overview

    This video provides an overview of the entire course.
    This video provides an overview of the entire course.
    TODOS
    4 min
    30 may 2017
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  • 2. The Anaconda Distribution

    2. The Anaconda Distribution

    Explain what Anaconda Distribution is and why we are using it in this course. Also show how to get and install the software.
    Explain what Anaconda Distribution is and why we are using it in this course. Also show how to get and install the software.
    TODOS
    8 min
    30 may 2017
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  • 3. Introduction to the Jupyter Notebook

    3. Introduction to the Jupyter Notebook

    Introduce the computing environment in which we will work for the rest of the course.
    Introduce the computing environment in which we will work for the rest of the course.
    TODOS
    10 min
    29 may 2017
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  • 4. Using the Jupyter Notebook

    4. Using the Jupyter Notebook

    Use the Jupyter notebook for basic Python code and explain the basics of using markdown and code cells in the Jupyter Notebook.
    Use the Jupyter notebook for basic Python code and explain the basics of using markdown and code cells in the Jupyter Notebook.
    TODOS
    12 min
    30 may 2017
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  • 5. NumPy: Python's Vectorization Solution

    5. NumPy: Python's Vectorization Solution

    Explain what Numpy is, the problem it solves and why it is important for Python's Data Stack.
    Explain what Numpy is, the problem it solves and why it is important for Python's Data Stack.
    TODOS
    8 min
    30 may 2017
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  • 6. NumPy Arrays: Creation, Methods and Attributes

    6. NumPy Arrays: Creation, Methods and Attributes

    Introduce arrays, the main objects in Numpy, and how to create and use them.
    Introduce arrays, the main objects in Numpy, and how to create and use them.
    TODOS
    23 min
    30 may 2017
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  • 7. Using NumPy for Simulations

    7. Using NumPy for Simulations

    Introduce with an example one of the common uses of Numpy: doing simulations.
    Introduce with an example one of the common uses of Numpy: doing simulations.
    TODOS
    12 min
    30 may 2017
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  • 8. The Pandas Library

    8. The Pandas Library

    Explain what pandas is and what we can do with it. An introduction to the main objects: Series and DataFrames.
    Explain what pandas is and what we can do with it. An introduction to the main objects: Series and DataFrames.
    TODOS
    14 min
    30 may 2017
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  • 9. Main Properties, Operations and Manipulations

    9. Main Properties, Operations and Manipulations

    Show how to use pandas Series and DataFrames with a real-world data set.
    Show how to use pandas Series and DataFrames with a real-world data set.
    TODOS
    14 min
    30 may 2017
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  • 10. Answering Simple Questions about a Dataset - Part 1

    10. Answering Simple Questions about a Dataset - Part 1

    Show the viewer how to use pandas by doing real-world data analysis tasks and answering questions.
    Show the viewer how to use pandas by doing real-world data analysis tasks and answering questions.
    TODOS
    12 min
    30 may 2017
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  • 11. Answering Simple Questions about a Dataset - Part 2

    11. Answering Simple Questions about a Dataset - Part 2

    Show the viewer how to use pandas by doing real-world data analysis tasks and answering questions.
    Show the viewer how to use pandas by doing real-world data analysis tasks and answering questions.
    TODOS
    16 min
    30 may 2017
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  • 12. Basics of Matplotlib

    12. Basics of Matplotlib

    Explain to the viewer what matplotlib is and the main concepts needed for using it.
    Explain to the viewer what matplotlib is and the main concepts needed for using it.
    TODOS
    7 min
    30 may 2017
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  • 13. Pyplot

    13. Pyplot

    Explain what pyplot is, how to use the pyplot interface, and its limitations.
    Explain what pyplot is, how to use the pyplot interface, and its limitations.
    TODOS
    10 min
    30 may 2017
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  • 14. The Object Oriented Interface

    14. The Object Oriented Interface

    Explain how to use the Object-Oriented Interface and how it compares with the plyplot interface.
    Explain how to use the Object-Oriented Interface and how it compares with the plyplot interface.
    TODOS
    9 min
    30 may 2017
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  • 15. Common Customizations

    15. Common Customizations

    Show some of the common customizations that can be done to plots.
    Show some of the common customizations that can be done to plots.
    TODOS
    12 min
    30 may 2017
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  • 16. EDA with Seaborn and Pandas

    16. EDA with Seaborn and Pandas

    Explain what Exploratory Data Analysis (EDA) is and how to perform it in a real-world dataset; in the process, introduce the Seaborn plotting library.
    Explain what Exploratory Data Analysis (EDA) is and how to perform it in a real-world dataset; in the process, introduce the Seaborn plotting library.
    TODOS
    9 min
    30 may 2017
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  • 17. Analysing Variables Individually

    17. Analysing Variables Individually

    Show how to analyze and make sense of individual variables depending on their type.
    Show how to analyze and make sense of individual variables depending on their type.
    TODOS
    17 min
    30 may 2017
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  • 18. Relationships between Variables

    18. Relationships between Variables

    Show how to produce the main plots used to show relationships between variables.
    Show how to produce the main plots used to show relationships between variables.
    TODOS
    15 min
    30 may 2017
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  • 19. SciPy and the Statistics Sub-Package

    19. SciPy and the Statistics Sub-Package

    Give a quick introduction to the Scipy package and all the different sub-packages it contains.
    Give a quick introduction to the Scipy package and all the different sub-packages it contains.
    TODOS
    4 min
    30 may 2017
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  • 20. Alcohol Consumption - Confidence Intervals and Probability Calculations

    20. Alcohol Consumption - Confidence Intervals and Probability Calculations

    Show how to perform statistical calculations with the stats package like confidence intervals and probabilities of events.
    Show how to perform statistical calculations with the stats package like confidence intervals and probabilities of events.
    TODOS
    11 min
    30 may 2017
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  • 21. Hypothesis Testing - Does Alcohol Consumption Affect Academic Performance?

    21. Hypothesis Testing - Does Alcohol Consumption Affect Academic Performance?

    Explain how to perform one of the most common statistical tests using the stats package.
    Explain how to perform one of the most common statistical tests using the stats package.
    TODOS
    8 min
    30 may 2017
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  • 22. Hypothesis Testing - Do Male Teenagers Drink More Than Females?

    22. Hypothesis Testing - Do Male Teenagers Drink More Than Females?

    Show how to perform a chi-square test using the stats package.
    Show how to perform a chi-square test using the stats package.
    TODOS
    5 min
    30 may 2017
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  • 23. Introduction to Predictive Analytics Models

    23. Introduction to Predictive Analytics Models

    Present an overview of the section. Discuss the concepts of Predictive Analytics and its relationship with Machine Learning and give some characteristics of ML models.
    Present an overview of the section. Discuss the concepts of Predictive Analytics and its relationship with Machine Learning and give some characteristics of ML models.
    TODOS
    6 min
    30 may 2017
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  • 24. The Scikit-Learn Library - Building a Simple Predictive Model

    24. The Scikit-Learn Library - Building a Simple Predictive Model

    Introduce the Scikit-Learn library and show the workflow traditionally used to build a Predictive Model with this library.
    Introduce the Scikit-Learn library and show the workflow traditionally used to build a Predictive Model with this library.
    TODOS
    7 min
    30 may 2017
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    • Become a Python Data Analyst
    Interés general
    20171 temporada
    This course introduces you to the main libraries of Python's Data Science stack. Taking an applied approach, it provides examples using real-world datasets to show you how to effectively use Python's tools to process, visualize and analyze data. It contains all you need to start analyzing data with Python and provides the foundation for more advanced topics like Predictive Analytics.
    Creadores y reparto
    Reparto
    Alvaro Fuentes
    Estudio
    Packt Publishing
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