Intro to Python for Data Science
Python is a general-purpose programming language that is becoming more and more popular for doing data science.
Критерий завершения
Course completed
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Python Basics
An introduction to the basic concepts of Python. Learn how to use Python both interactively and through a script. Create your first variables and acquaint yourself with Python's basic data types.
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Hello Python!
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The Python Interface
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When to use Python
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Any comments?
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Python as a calculator
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Variables & Types
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Variable Assignment
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Calculations with variables
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Other variable types
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Guess the type
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Operations with other types
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Type conversion
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Can Python handle everything?
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Python Lists
Learn to store, access and manipulate data in lists: the first step towards efficiently working with huge amounts of data.
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Lists, what are they?
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Create a list
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Create list with different types
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Select the valid list
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List of lists
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Subsetting lists
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Subset and conquer
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Subset and calculate
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Slicing and dicing
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Slicing and dicing (2)
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Subsetting lists of lists
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List Manipulation
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Replace list elements
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Extend a list
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Delete list elements
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Inner workings of lists
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Functions and Packages
To leverage the code that brilliant Python developers have written, you'll learn about using functions, methods and packages. This will help you to reduce the amount of code you need to solve challenging problems!
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Functions
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Familiar functions
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Help!
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Multiple arguments
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Methods
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String Methods
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List Methods
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List Methods (2)
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Packages
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Import package
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Selective import
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Different ways of importing
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NumPy
NumPy is a Python package to efficiently do data science. Learn to work with the NumPy array, a faster and more powerful alternative to the list, and take your first steps in data exploration.
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NumPy
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Your First NumPy Array
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Baseball players' height
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Baseball player's BMI
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Lightweight baseball players
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NumPy Side Effects
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Subsetting NumPy Arrays
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2D NumPy Arrays
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Your First 2D NumPy Array
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Subsetting 2D NumPy Arrays
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2D Arithmetic
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NumPy: Basic Statistics
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Average versus median
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Explore the baseball data
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Blend it all together
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