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.

Master the basics of data analysis in Python. Expand your skillset by learning scientific computing with NumPy.

Discover how to use Python for data science, learning about the ways to store and manipulate data in the environment to begin conducting your own analyses.

Introduction to Python

In this course you will begin learning the art and science of data exploration. You'll also become familiar with some of the most widely used visualization packages in data science. You'll get the chance to explore a number of fun & interesting datasets such as the <a href='https://www.kaggle.com/census/2013-american-community-survey' target="_blank">2013 American Community Survey</a>, pigeon racing data, data on the length of chopsticks and Marijuana prices in the US. After completing the course, you'll be able to upload your first <a href='https://www.kaggle.com/scripts' target="_blank">Kaggle Script</a>. <hr> Bonus Chapter: Once you have finished your exercises on DataCamp it's time to start building a data science portfolio with your new skills! In this bonus chapter, you'll be given the chance to publish analyses on Kaggle Scripts that you've personalized with information from your own life. <ul> <li><a href='https://www.kaggle.com/benhamner/d/kaggle/us-baby-names/babies-named-benjamin-over-time'>(Basic) Visualize a dataset on US Baby Names to learn the popularity of your name or a friend's name in the USA over the past 100+ years.</a></li> <li><a href='https://www.kaggle.com/benhamner/d/kaggle/college-scorecard/exploring-your-college-duke-university'>(Intermediate) Create a polished analysis in RMarkdown that walks readers through recent changes at the college you attended or would like to attend. You will explore changes in enrollment, tuition, admissions rate, and degree types.</a></li> <li>(Advanced) Each of Ben's scripts end with suggestions for creating an even meatier analysis. Which ones can you use to extend your work?</li> </ul> To start each exercise, follow the link to a script that has been created by Kaggle CTO Ben Hamner. Review the code or output to find instructions for creating a custom analysis. Then click Fork on the script to create an editable copy and get started.

Data Exploration With Kaggle Scripts

Always wanted to compete in a <a href='https://www.kaggle.com/?utm_medium=partner&utm_source=datacamp.com&utm_campaign=datacamp+python' target="_blank">Kaggle</a> competition but not sure you have the right skillset? This interactive tutorial by Kaggle and DataCamp on Machine Learning offers the solution. Step-by-step you will learn through fun coding exercises how to predict survival rate for Kaggle's Titanic competition using Machine Learning techniques. Upload your results and see your ranking go up! New to Python? Give our <a href='https://www.datacamp.com/courses/intro-to-python-for-data-science' target="_blank">Introduction to Python for Data Science</a> course a try.

Kaggle Python Tutorial on Machine Learning

Most of the world's data are not sorted in a clean and organized fashion; nor are they easy to process. As a data scientist, you need to know what the standards for tidy data are and how to create tidy datasets from messy ones. This mini-course will prepare you for these tasks.

Tidy Data in Python Mini-Course

The best marketers and growth hackers are data-driven. They quickly pull data about marketing campaigns, customers, ... from databases on their own and use this information to run more profitable campaigns. In this interactive tutorial by DataCamp, you will learn through fun interactive exercises how you can use the powerful Structured Query Language or SQL to communicate with a relational database. Step-by-step, you will learn how to retrieve and filter data from a database that contains data on bank clients and direct marketing campaigns.

SQL Tutorial for Marketers

Learning Python is crucial for any aspiring data science practitioner. Learn to visualize real data with Matplotlib's functions and get acquainted with data structures such as the dictionary and the pandas DataFrame. After covering key concepts such as boolean logic, control flow, and loops in Python, you'll be ready to blend together everything you've learned to solve a case study using hacker statistics.

Level up your data science skills by creating visualizations using Matplotlib and manipulating DataFrames with pandas.

In this intermediate Python course, learn to visualize real data with Matplotlib's functions and get to know new data structures such as the pandas DataFrame.

Intermediate Python

If you've ever wanted to understand more about social networks, information networks, or even the neural networks of our brains, then you need to know network science! It will demonstrate network analysis using several R packages, including dplyr, ggplot2, igraph, ggraph as well as visNetwork. You will take on the role of Interpol Analyst and investigate the terrorist network behind the Madrid train bombing in 2004. Following the course, you will be able to analyse any network with basic centrality and similarity measures and create beautiful and interactive network visualizations.

Learn how to analyze and visualize network data in the R programming language using the tidyverse approach.

Network Analysis in the Tidyverse

Begin your journey into Data Science! Even if you've never written a line of code in your life, you'll be able to follow this course and witness the power of Python to perform Data Science. You'll use data to solve the mystery of Bayes, the kidnapped Golden Retriever, and along the way you'll become familiar with basic Python syntax and popular Data Science modules like Matplotlib (for charts and graphs) and pandas (for tabular data).

Dive into data science using Python and learn how to effectively analyze and visualize your data. No coding experience or skills needed.

Dive into data science using Python and learn how to effectively analyze and visualize your data using Pandas and Matplotlib. No coding experience needed.

Introduction to Data Science in Python

Visualizing data in plots and figures exposes the underlying patterns in the data and provides insights. Good visualizations also help you communicate your data to others, and are useful to data analysts and other consumers of the data. In this course, you will learn how to use Matplotlib, a powerful Python data visualization library. Matplotlib provides the building blocks to create rich visualizations of many different kinds of datasets. You will learn how to create visualizations for different kinds of data and how to customize, automate, and share these visualizations.

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