Data Research Exploration Techniques

Data Research    |    Intermediate
  • 11 videos | 49m 15s
  • Includes Assessment
  • Earns a Badge
Likes 12 Likes 12
This course explores EDA (exploratory data analysis) and data research techniques necessary to communicate with data management professionals involved in application, implementation, and facilitation of the data research mechanism. You will examine EDA as an important way to analyze extracted data by applying various visual and quantitative methods. In this 10-video course, learners acquire data exploration techniques to derive different data dimensions to derive value from the data. You will learn proper methodologies and principles for various data exploration techniques, analysis, decision-making, and visualizations to gain valuable insights from the data. This course covers how to practically implement data exploration by using R random number generator, Python, linear algebra, and plots. You will use EDA to build learning sets which can be utilized by various machine learning algorithms or even statistical modeling. You will learn to apply univariate visualization, and to use multivariate visualizations to identify the relationship among the variables. Finally, the course explores dimensionality reduction to apply different dimension reduction algorithms to deduce the data in a state which is useful for analytics.

WHAT YOU WILL LEARN

  • specify the essential features and benefits provided by implementing exploratory data analysis
    recognize the prominent approaches that can be adopted to implement data exploration
    install and prepare R for data exploration
    demonstrate how to implement data exploration using R
    implement data exploration using plots in R
  • specify the essential packages provided by Python that can be used to explore data
    implement data exploration using Python's data exploration packages
    describe the approach of implementing data research using linear algebra
    work with vectors and metrics using Python and R
    explore data using R, explore data with Python packages, and work with vectors using Python

IN THIS COURSE

  • 1m 46s
  • 4m 11s
    After completing this video, you will be able to specify the essential features and benefits provided by implementing exploratory data analysis. FREE ACCESS
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    3.  Data Exploration Types
    5m 13s
    After completing this video, you will be able to recognize the prominent approaches that can be adopted to implement data exploration. FREE ACCESS
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    4.  Working with R
    8m 44s
    In this video, you will learn how to install and prepare R for data exploration. FREE ACCESS
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    5.  Data Exploration in R
    4m 21s
    In this video, you will learn how to implement data exploration using R. FREE ACCESS
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    6.  Data Exploration Using Plots
    3m 14s
    Learn how to implement data exploration using plots in R. FREE ACCESS
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    7.  Python Packages for Data Exploration
    4m 31s
    After completing this video, you will be able to specify the essential packages provided by Python that can be used to explore data. FREE ACCESS
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    8.  Data Exploration Using Python
    3m 53s
    In this video, you will learn how to implement data exploration using Python's data exploration packages. FREE ACCESS
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    9.  Data Research Using Linear Algebra
    3m
    After completing this video, you will be able to describe the approach of implementing data research using linear algebra. FREE ACCESS
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    10.  Linear Algebra for Data Research
    6m 36s
    In this video, you will learn how to work with vectors and metrics using Python and R. FREE ACCESS
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    11.  Exercise: R and Python for Data Exploration
    3m 49s
    Learn how to explore data using R, explore data with Python packages, and work with vectors in Python. FREE ACCESS

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