Learn Python using Statistics: Data Analysis & Data Science

Learn Python using Statistics: Data Analysis & Data Science

What you’ll learn

  • Real-world use cases of Python and its versatility.
  • Installation of Python on both Mac and Windows operating systems.
  • Fundamentals of programming with Python, including variables and data types.
  • Working with various operators in Python to perform operations.
  • Handling data using essential data structures like lists, tuples, sets, and dictionaries.
  • Utilizing functions and working with parameters and arguments.
  • Employing filter, map, and zip functions for data processing.
  • Exploring analytical and aggregate functions for data analysis.
  • Using built-in functions for regular expressions and handling special characters and sets.
  • Iterating over elements using for loops and while loops.
  • Understanding the object-oriented programming (OOP) concepts and principles.
  • Working with date and time classes, including TimeDelta for time manipulation.
  • Fundamental concepts and importance of statistics in various fields.
  • How to use statistics for effective data analysis and decision-making.
  • Introduction to Python for statistical analysis, including data manipulation and visualization.
  • Different types of data and their significance in statistical analysis.
  • Measures of central tendency, spread, dependence, shape, and position.
  • How to calculate and interpret standard scores and probabilities.
  • Key concepts in probability theory, set theory, and conditional probability.
  • Understanding Bayes’ Theorem and its applications.
  • Permutations, combinations, and their role in solving real-world problems.
  • Practical knowledge of various statistical tests, including t-tests, chi-squared tests, and ANOVA, for hypothesis testing and inference.

How to Enroll Learn Python using Statistics: Data Analysis & Data Science course?

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