Understanding and Visualizing Data with Python

This course is part of Statistics with Python Specialization

Instructors: Brenda Gunderson +2 more

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What you'll learn

  •   Properly identify various data types and understand the different uses for each
  •   Create data visualizations and numerical summaries with Python
  •   Communicate statistical ideas clearly and concisely to a broad audience
  •   Identify appropriate analytic techniques for probability and non-probability samples

    • Skills you'll gain

  •   Statistical Inference
  •   Exploratory Data Analysis
  •   Data Analysis
  •   Statistical Analysis
  •   Data Visualization
  •   NumPy
  •   Sampling (Statistics)
  •   Statistical Methods
  •   Probability & Statistics
  •   Matplotlib
  •   Descriptive Statistics
  •   Data Collection
  •   Jupyter
  •   Statistical Visualization
  •   Statistics
  •   Python Programming
  •   Histogram
  •   Data Visualization Software

    • There are 4 modules in this course

    At the end of each week, learners will apply the statistical concepts they’ve learned using Python within the course environment. During these lab-based sessions, learners will discover the different uses of Python as a tool, including the Numpy, Pandas, Statsmodels, Matplotlib, and Seaborn libraries. Tutorial videos are provided to walk learners through the creation of visualizations and data management, all within Python. This course utilizes the Jupyter Notebook environment within Coursera.

    WEEK 2 - UNIVARIATE DATA

    WEEK 3 - MULTIVARIATE DATA

    WEEK 4 - POPULATIONS AND SAMPLES

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