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Data Scientist with Python

Gain the career-building Python skills you need to succeed in the exciting field of data science—from data manipulation to machine learning! In this track, you’ll learn how this versatile language allows you to import, clean, manipulate, and visualize data—all integral skills for any aspiring data professional or researcher. Through interactive exercises, you’ll get hands-on with some of the most popular Python libraries, including pandas, NumPy, Matplotlib, and many more. You’ll then work with real-world datasets to learn the statistical and machine learning techniques you need to perform hypothesis testing and build predictive models. Start this track, grow your Python skills, and begin your journey to becoming a confident data scientist.

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Loved by learners at thousands of companies

1
Python
Introduction to Python

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

4 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist at DataCamp

2
Python
Intermediate Python

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

4 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist at DataCamp

3
Python
Investigating Netflix Movies and Guest Stars in The Office

Apply the foundational Python skills you learned in Introduction to Python and Intermediate Python by manipulating and visualizing movie and TV data.

2 hours

Justin Saddlemyer Headshot

Justin Saddlemyer

Justin is a Workspace Content Developer at DataCamp. He holds ...

4
Python
Data Manipulation with pandas

Use the world’s most popular Python data science package to manipulate data and calculate summary statistics.

4 hours

Richie Cotton Headshot

Richie Cotton

Data Evangelist at DataCamp

5
Python
Joining Data with pandas

Learn to combine data from multiple tables by joining data together using pandas.

4 hours

Aaren Stubberfield Headshot

Aaren Stubberfield

Manager, Supply Chain Analytics @ Ingredion Incorporated

6
Python
The GitHub History of the Scala Language

Find the true Scala experts by exploring its development history in Git and GitHub.

2 hours

Anita Sarma Headshot

Anita Sarma

Associate Professor at Oregon State University

7
Python
Introduction to Data Visualization with Matplotlib

Learn how to create, customize, and share data visualizations using Matplotlib.

4 hours

Ariel Rokem Headshot

Ariel Rokem

Senior Data Scientist, University of Washington

8
Python
Introduction to Data Visualization with Seaborn

Learn how to create informative and attractive visualizations in Python using the Seaborn library.

4 hours

DataCamp Content Creator

Course Instructor

9
Python
Introduction to NumPy

Learn how to use NumPy arrays in Python to perform mathematical operations and wrangle data with the best of them!

4 hours

Izzy Weber Headshot

Izzy Weber

Curriculum Manager, DataCamp

10
Python
Python Data Science Toolbox (Part 1)

Learn the art of writing your own functions in Python, as well as key concepts like scoping and error handling.

3 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist at DataCamp

11
Python
The Android App Market on Google Play

Load, clean, and visualize scraped Google Play Store data to gain insights into the Android app market.

2 hours

Lavanya Gupta Headshot

Lavanya Gupta

Machine Learning Engineer at PropTiger.com

12
Python
Python Data Science Toolbox (Part 2)

Continue to build your modern Data Science skills by learning about iterators and list comprehensions.

4 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist at DataCamp

13
Python
Intermediate Data Visualization with Seaborn

Use Seaborn's sophisticated visualization tools to make beautiful, informative visualizations with ease.

4 hours

Chris Moffitt Headshot

Chris Moffitt

Creator of Practical Business Python

14
Python
A Visual History of Nobel Prize Winners

Explore a dataset from Kaggle containing a century's worth of Nobel Laureates. Who won? Who got snubbed?

2 hours

Rasmus Bååth Headshot

Rasmus Bååth

Data Science Lead at castle.io

15
Python
Data Manipulation with Python
16
Python
Introduction to Importing Data in Python

Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.

3 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist at DataCamp

17
Python
Intermediate Importing Data in Python

Improve your Python data importing skills and learn to work with web and API data.

2 hours

Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist at DataCamp

18
Python
Cleaning Data in Python

Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!

4 hours

Adel Nehme Headshot

Adel Nehme

Content Developer @ DataCamp

19
Python
Working with Dates and Times in Python

Learn how to work with dates and times in Python.

4 hours

Max Shron Headshot

Max Shron

Data Scientist and Author

20
Python
Importing & Cleaning Data with Python
21
Python
Writing Functions in Python

Learn to use best practices to write maintainable, reusable, complex functions with good documentation.

4 hours

Shayne Miel Headshot

Shayne Miel

Director of Software Engineering @ American Efficient

22
Python
Python Programming
23
Python
Exploratory Data Analysis in Python

Learn how to explore, visualize, and extract insights from data.

4 hours

Allen Downey Headshot

Allen Downey

Professor, Olin College

24
Python
Analyzing Police Activity with pandas

Explore the Stanford Open Policing Project dataset and analyze the impact of gender on police behavior using pandas.

4 hours

Kevin Markham Headshot

Kevin Markham

Founder of Data School

25
Python
Introduction to Statistics in Python

Grow your statistical skills and learn how to collect, analyze, and draw accurate conclusions from data using Python.

4 hours

Maggie Matsui Headshot

Maggie Matsui

Curriculum Manager at DataCamp

26
Python
Introduction to Regression with statsmodels in Python

Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in Python.

4 hours

Maarten Van den Broeck Headshot

Maarten Van den Broeck

Content Developer at DataCamp

27
Python
Sampling in Python

Learn to draw conclusions from limited data using Python and statistics. This course covers everything from random sampling to stratified and cluster sampling.

4 hours

James Chapman Headshot

James Chapman

Content Developer, DataCamp

28
Python
Hypothesis Testing in Python

Learn how and when to use common hypothesis tests like t-tests, proportion tests, and chi-square tests in Python.

4 hours

James Chapman Headshot

James Chapman

Content Developer, DataCamp

29
Python
Dr. Semmelweis and the Discovery of Handwashing

Reanalyse the data behind one of the most important discoveries of modern medicine: handwashing.

2 hours

Rasmus Bååth Headshot

Rasmus Bååth

Data Science Lead at castle.io

30
Python
Supervised Learning with scikit-learn

Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!

4 hours

George Boorman Headshot

George Boorman

Core Curriculum Manager, DataCamp

31
Python
Predicting Credit Card Approvals

Build a machine learning model to predict if a credit card application will get approved.

2 hours

Sayak Paul Headshot

Sayak Paul

Machine Learning Engineer at Carted

32
Python
Unsupervised Learning in Python

Learn how to cluster, transform, visualize, and extract insights from unlabeled datasets using scikit-learn and scipy.

4 hours

Benjamin Wilson Headshot

Benjamin Wilson

Director of Research at lateral.io

33
Python
Machine Learning with Tree-Based Models in Python

In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

5 hours

Elie Kawerk Headshot

Elie Kawerk

Data Scientist at Mirum Agency

34
Python
Cluster Analysis in Python

In this course, you will be introduced to unsupervised learning through techniques such as hierarchical and k-means clustering using the SciPy library.

4 hours

Shaumik Daityari Headshot

Shaumik Daityari

Business Analyst at American Express

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