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Introduction to Python

4.7+
1421 reviews
Beginner

Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.

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4 Hours11 Videos57 Exercises4,905,852 Learners

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Course Description

An Introduction to Python

Python has grown to become the market leader in programming languages and the language of choice for data analysts and data scientists. Demand for data skills is rising because companies want to gain actionable insights from their data.

Discover the Python Basics

This is a Python course for beginners, and we designed it for people with no prior Python experience. It is even suitable if you have no coding experience at all. You will cover the basics of Python, helping you understand common, everyday functions and applications, including how to use Python as a calculator, understanding variables and types, and building Python lists. The first half of this course prepares you to use Python interactively and teaches you how to store, access, and manipulate data using one of the most popular programming languages in the world.

Explore Python Functions and Packages

The second half of the course starts with a view of how you can use functions, methods, and packages to use code that other Python developers have written. As an open-source language, Python has plenty of existing packages and libraries that you can use to solve your problems.

Get Started with NumPy

NumPy is an essential Python package for data science. You’ll finish this course by learning to use some of the most popular tools in the NumPy array and start exploring data in Python.
  1. 1

    Python Basics

    Free

    An introduction to the basic concepts of Python. Learn how to use Python interactively and by using a script. Create your first variables and acquaint yourself with Python's basic data types.

    Play Chapter Now
    Hello Python!
    50 xp
    When to use Python?
    50 xp
    The Python Interface
    100 xp
    Any comments?
    100 xp
    Python as a calculator
    100 xp
    Variables and Types
    50 xp
    Variable Assignment
    100 xp
    Calculations with variables
    100 xp
    Other variable types
    100 xp
    Guess the type
    50 xp
    Operations with other types
    100 xp
    Type conversion
    100 xp
    Can Python handle everything?
    50 xp
  2. 2

    Python Lists

    Learn to store, access, and manipulate data in lists: the first step toward efficiently working with huge amounts of data.

    Play Chapter Now
    Python Lists
    50 xp
    Create a list
    100 xp
    Create list with different types
    100 xp
    Select the valid list
    50 xp
    List of lists
    100 xp
    Subsetting Lists
    50 xp
    Subset and conquer
    100 xp
    Subset and calculate
    100 xp
    Slicing and dicing
    100 xp
    Slicing and dicing (2)
    100 xp
    Subsetting lists of lists
    50 xp
    Manipulating Lists
    50 xp
    Replace list elements
    100 xp
    Extend a list
    100 xp
    Delete list elements
    50 xp
    Inner workings of lists
    100 xp
  3. 3

    Functions and Packages

    You'll learn how to use functions, methods, and packages to efficiently leverage the code that brilliant Python developers have written. The goal is to reduce the amount of code you need to solve challenging problems!

    Play Chapter Now
    Functions
    50 xp
    Familiar functions
    100 xp
    Help!
    50 xp
    Multiple arguments
    100 xp
    Methods
    50 xp
    String Methods
    100 xp
    List Methods
    100 xp
    List Methods (2)
    100 xp
    Packages
    50 xp
    Import package
    100 xp
    Selective import
    100 xp
    Different ways of importing
    50 xp
  4. 4

    NumPy

    NumPy is a fundamental Python package to efficiently practice data science. Learn to work with powerful tools in the NumPy array, and get started with data exploration.

    Play Chapter Now
    NumPy
    50 xp
    Your First NumPy Array
    100 xp
    Baseball players' height
    100 xp
    Baseball player's BMI
    100 xp
    Lightweight baseball players
    100 xp
    NumPy Side Effects
    50 xp
    Subsetting NumPy Arrays
    100 xp
    2D NumPy Arrays
    50 xp
    Your First 2D NumPy Array
    100 xp
    Baseball data in 2D form
    100 xp
    Subsetting 2D NumPy Arrays
    100 xp
    2D Arithmetic
    100 xp
    NumPy: Basic Statistics
    50 xp
    Average versus median
    100 xp
    Explore the baseball data
    100 xp
    Blend it all together
    100 xp

In the following tracks

Data Analyst with PythonData EngineerData Scientist with PythonData Scientist Professional with PythonPython FundamentalsPython Programmer

Datasets

MLB (baseball)FIFA (soccer)

Collaborators

Vincent Vankrunkelsven
Filip Schouwenaars
Hugo Bowne-Anderson HeadshotHugo Bowne-Anderson

Data Scientist at DataCamp

Hugo is a data scientist, educator, writer and podcaster formerly at DataCamp. His main interests are promoting data & AI literacy, helping to spread data skills through organizations and society and doing amateur stand up comedy in NYC. If you want to know what he likes to talk about, definitely check out DataFramed, the DataCamp podcast, which he hosted and produced.
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Don’t just take our word for it

*4.7
from 1421 reviews
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  • Jorge B.
    about 14 hours

    Excelent! I Liked very much because you go straightforward to data analysis and don't lost time teaching us so many that we don't need

  • Mert D.
    about 22 hours

    Good

  • Sergio L.
    3 days

    Nice

  • Pranay N.
    4 days

    Everything is great the teaching style the content U recommend u people to use some different style of slides and animations It would make the content more intuitive.

  • Thomas F.
    5 days

    Efficient course with little wasted motion.

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"Excelent! I Liked very much because you go straightforward to data analysis and don't lost time teaching us so many that we don't need"

Jorge B.

"Good"

Mert D.

"Nice"

Sergio L.

FAQs

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