Introduction to Python
Master the basics of data analysis with Python in just four hours. This online course will introduce the Python interface and explore popular packages.Start Course for Free
4 Hours11 Videos57 Exercises4,792,313 Learners4700 XPData Analyst with Python TrackData Engineer TrackData Scientist with Python TrackData Scientist Professional with Python TrackPython Fundamentals TrackPython Programmer Track
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An Introduction to PythonPython 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 BasicsThis 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 PackagesThe 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 NumPyNumPy 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.
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.Hello Python!50 xpThe Python Interface100 xpWhen to use Python?50 xpAny comments?100 xpPython as a calculator100 xpVariables and Types50 xpVariable Assignment100 xpCalculations with variables100 xpOther variable types100 xpGuess the type50 xpOperations with other types100 xpType conversion100 xpCan Python handle everything?50 xp
Learn to store, access, and manipulate data in lists: the first step toward efficiently working with huge amounts of data.Python Lists50 xpCreate a list100 xpCreate list with different types100 xpSelect the valid list50 xpList of lists100 xpSubsetting Lists50 xpSubset and conquer100 xpSubset and calculate100 xpSlicing and dicing100 xpSlicing and dicing (2)100 xpSubsetting lists of lists50 xpManipulating Lists50 xpReplace list elements100 xpExtend a list100 xpDelete list elements50 xpInner workings of lists100 xp
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!
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.NumPy50 xpYour First NumPy Array100 xpBaseball players' height100 xpBaseball player's BMI100 xpLightweight baseball players100 xpNumPy Side Effects50 xpSubsetting NumPy Arrays100 xp2D NumPy Arrays50 xpYour First 2D NumPy Array100 xpBaseball data in 2D form100 xpSubsetting 2D NumPy Arrays100 xp2D Arithmetic100 xpNumPy: Basic Statistics50 xpAverage versus median100 xpExplore the baseball data100 xpBlend it all together100 xp
In the following tracksData Analyst with PythonData EngineerData Scientist with PythonData Scientist Professional with PythonPython FundamentalsPython Programmer
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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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Materials are introduced through short videos, which are very clear and informative. Each video is followed by several well-conceived exercises.
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"Materials are introduced through short videos, which are very clear and informative. Each video is followed by several well-conceived exercises."
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