Loved by learners at thousands of companies
Python is a general-purpose programming language that is becoming ever more popular for data science. Companies worldwide are using Python to harvest insights from their data and gain a competitive edge. Unlike other Python tutorials, this course focuses on Python specifically for data science. In our Introduction to Python course, you’ll learn about powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses. Start DataCamp’s online Python curriculum now.
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 PackagesFree
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
Data Scientist at DataCamp
Hugo is a data scientist, educator, writer and podcaster 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 hosts and produces: https://www.datacamp.com/community/podcast
What do other learners have to say?
I've used other sites—Coursera, Udacity, things like that—but DataCamp's been the one that I've stuck with.
Devon Edwards Joseph
Lloyds Banking Group
DataCamp is the top resource I recommend for learning data science.
Harvard Business School
DataCamp is by far my favorite website to learn from.
Decision Science Analytics, USAA