Introduction to Python
About this course
Your Python data analysis mastery journey begins here. Grow your scientific computing knowledge with NumPy.
4 hoursGo to course
Ready to start your Python journey? In this track, you’ll learn the basics including how to clean data so it's ready for analysis, get started with data visualization libraries, and start writing your own Python functions.
Gain your Python career programming skills here where you cover the fundamentals of software development in python, data wrangling, and advanced data analysis with Python.
Begin your journey into data science with Python. Learn to analyze and visualize your data.
Get to know different data types. Leverage Python to solve your data problems.
Write more more effective and efficient code using Python's in-built features.
Work with movie reviews datasets and become an expert in using regular expressions.
Retrieve and parse information from the internet. Discover the Python library scrapy.
Automate repetitive tasks and run programs on clusters and clouds with Unix.
Solve your data science problems. Discover modularity, documentation, and automated testing.
Create your own Python package. Use setuptools and twine to publish your packages to PyPI.
Start your journey into unit testing. Write your own write unit tests in Python.
Create classes in Python. Leverage principles to reuse and optimize code.
This collection of courses will take you from zero to hero providing you with the Python skills needed for your new career as a data scientist. Learn skills such as importing, cleaning, manipulation, and visualizing data. Everything you need to become a data professional.
Build your data science portfolio. Use everything you have learned in Python to visualize Netflix data.
Use Python to load, clean, and scrape data. Practice using Google Play Store data to visualize market insights.
Learn to handle multiple DataFrames with Fandas. Combine, organize, join, and reshape data from the City Of Chicago.
Get to know the history of Scala projects. Learn how to identify who made changes and what changes they made.
Your Matplotlib journey begins here. Learn how to visualize data from a variety of sources.
Your journey into Seaborn starts here. Learn how to create and customize visualizations in Python.
Continue your Seaborn journey. Learn to customize your plots to your data sets to create meaningful visualizations.
Use Kaggle to examine a dataset of previous Nobel Prize Nominees. Learn how to visualize historical datasets.
Start your journey into data importing in Python. Learn to import from Excel, SQL, SAS, and the web.
Develop your ability to import data in Python. Work with web and API data in Python.
Get the most out of your analysis by cleaning your data. Understand how to handle missing data or improper data types.
Grow your data analysis skills. Use regression models to make predictions in Python.
Work with Pandas to import, clean, shape, and visualize data from the Stanford Open Policing Project.
Start thinking statistically in Python. Learn to better understand your data and its features.
Your path to statistical thinking continues here. Learn how to perform parameter estimation and hypothesis testing.
Practice your data analysis skills while using historical data to understand the effect of handwashing.
Build and tune predictive models. Discover supervised learning in Python.
Practice predicting outcomes using credit card applications. Build and test your own machine learning model.
Continue your journey in using Python for analysis. Extract insights from unlabeled datasets using scikit-learn and scipy.
Discover machine learning with Python. Create your own train decision trees and models with scikit-learn.
5 hoursGo to course
Practice machine learning in Python. Build a baseline model using school budget data.
Start your journey into unsupervised learning with the SciPy library. Use various clustering algorithms on your data.
If you're new to Python, make sure you start here with our most popular track for beginners.Start Learning Free
Taking your first Python course is just the beginning of a journey towards understanding and using Python in your professional life. If you’re serious about launching a career with Python or changing your career path, you can take one of our Tracks, which are designed to provide in-depth learning and ensure that you’re ready to apply your Python skills in the world of work.
Once you feel ready, demonstrate your Python skills in our assessments that build towards professional certification as a data scientist or a data analyst. These certifications are based on an in-depth analysis of the skills required within today’s jobs market and are purposefully designed to test and demonstrate that you’re ready for a demanding job in the industry.
DataCamp's interactive and hands-on learning method features engaging tutorials, bite-sized challenges, and practical projects. After you choose a course, you'll find a collection of well-categorized topics and subtopics. You can decide where to start based on your interests or follow our recommendation.
In each learning session, an instructor explains a concept and the code snippet you'll be using. Next, you'll put this code through its paces in DataCamp's dedicated coding platform.
Learn coding and data science with Python in a fun way and you'll never get bored. All you need is an internet connection, a browser, and a thirst for knowledge.
DataCamp is home to a huge collection of Python resources to support you on your learning path and throughout your career. These include:
So whether you’re mastering the basics of importing data or wrapping your head around advanced NLP tasks in Python, we’ve got what you need to make learning simple.
Join over 9 million learners and go further, faster, with DataCamp.Start Learning for Free