CAREER TRACK

Data Scientist with Python

A Data Scientist combines statistical and machine learning techniques with Python programming to analyze and interpret complex data.

Join

Python
100 hours
26 Courses
$118,000/year

1

Introduction to Python

Master the basics of data analysis in Python. Expand your skill set by learning scientific computing with numpy.

4 hours

Filip Schouwenaars

Data Science Instructor at DataCamp
2

Intermediate Python for Data Science

Level up your data science skills by creating visualizations using matplotlib and manipulating data frames with Pandas.

4 hours

Filip Schouwenaars

Data Science Instructor at DataCamp
3

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 Play preview

Hugo Bowne-Anderson

Data Scientist at DataCamp
4

Python Data Science Toolbox (Part 2)

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

4 hours Play preview

Hugo Bowne-Anderson

Data Scientist at DataCamp
5

Importing Data in Python (Part 1)

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

3 hours Play preview

Hugo Bowne-Anderson

Data Scientist at DataCamp
6

Importing Data in Python (Part 2)

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

2 hours Play preview

Hugo Bowne-Anderson

Data Scientist at DataCamp
7

Cleaning Data in Python

This course will equip you with all the skills you need to clean your data in Python.

4 hours Play preview

Daniel Chen

Data Science Consultant at Lander Analytics
8

pandas Foundations

Learn how to use the industry-standard pandas library to import, build, and manipulate DataFrames.

4 hours Play preview

Team Anaconda

Data Science Training
9

Manipulating DataFrames with pandas

You will learn how to tidy, rearrange, and restructure your data using versatile pandas DataFrames.

4 hours Play preview

Team Anaconda

Data Science Training
10

Merging DataFrames with pandas

This course is all about the act of combining, or merging, DataFrames, an essential part your Data Scientist's toolbox.

4 hours Play preview

Team Anaconda

Data Science Training
11

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 Play preview

Kevin Markham

Founder of Data School
12

Intro to SQL for Data Science

Master the basics of querying tables in relational databases such as MySQL, Oracle, SQL Server, and PostgreSQL.

4 hours

Nick Carchedi

Product Manager at DataCamp
13

Introduction to Relational Databases in SQL

Learn how to create one of the most efficient ways of storing data - relational databases!

4 hours

Timo Grossenbacher

Data Journalist at SRF Data
14

Introduction to Data Visualization with Python

Learn more complex data visualization techniques using Matplotlib and Seaborn.

4 hours Play preview

Team Anaconda

Data Science Training
15

Interactive Data Visualization with Bokeh

Learn how to create versatile and interactive data visualizations using Bokeh.

4 hours Play preview

Team Anaconda

Data Science Training
16

Statistical Thinking in Python (Part 1)

Build the foundation you need to think statistically and to speak the language of your data.

3 hours Play preview

Justin Bois

Lecturer at the California Institute of Technology
17

Statistical Thinking in Python (Part 2)

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

4 hours Play preview

Justin Bois

Lecturer at the California Institute of Technology
18

Joining Data in SQL

Join two or three tables together into one, combine tables using set theory, and work with subqueries in PostgreSQL.

5 hours Play preview

Chester Ismay

Head of Content Development (Belgium) at DataCamp
19

Introduction to Shell for Data Science

The Unix command line helps users combine existing programs in new ways, automate repetitive tasks, and run programs ...

4 hours

Greg Wilson

Co-founder of Software Carpentry
20

Conda Essentials

Learn how to easily manage your software using conda.

3 hours

David Mertz

Senior Data Science Trainer at Anaconda Inc.
21

Supervised Learning with scikit-learn

Learn how to build and tune predictive models and evaluate how well they will perform on unseen data.

4 hours Play preview

Hugo Bowne-Anderson

Data Scientist at DataCamp
22

Machine Learning with the Experts: School Budgets

Learn how to build a model to automatically classify items in a school budget.

4 hours Play preview

Peter Bull

Co-founder of DrivenData
23

Unsupervised Learning in Python

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

4 hours Play preview

Benjamin Wilson

Director of Research at lateral.io
24

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 sciki...

5 hours Play preview

Elie Kawerk

Data Scientist at Mirum Agency
25

Deep Learning in Python

Learn the fundamentals of neural networks and how to build deep learning models using Keras 2.0.

4 hours Play preview

Dan Becker

Data Scientist and contributor to Keras and TensorFlow libraries
26

Network Analysis in Python (Part 1)

This course will equip you with the skills to analyze, visualize, and make sense of networks using the NetworkX library.

4 hours Play preview

Eric Ma

Data Carpentry instructor and author of nxviz package
Statement of accomplishment

See all 26 courses

Filip Schouwenaars

Data Science Instructor at DataCamp

Hugo Bowne-Anderson

Data Scientist at DataCamp

Daniel Chen

Data Science Consultant at Lander Analytics

Team Anaconda

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Data Scientist with Python

Introduction to Python

Intermediate Python for Data Science

Python Data Science Toolbox (Part 1)

Python Data Science Toolbox (Part 2)

Importing Data in Python (Part 1)

Importing Data in Python (Part 2)

Cleaning Data in Python

pandas Foundations

Manipulating DataFrames with pandas

Merging DataFrames with pandas

Analyzing Police Activity with pandas

Intro to SQL for Data Science

Introduction to Relational Databases in SQL

Introduction to Data Visualization with Python

Interactive Data Visualization with Bokeh

Statistical Thinking in Python (Part 1)

Statistical Thinking in Python (Part 2)

Joining Data in SQL

Introduction to Shell for Data Science

Conda Essentials

Supervised Learning with scikit-learn

Machine Learning with the Experts: School Budgets

Unsupervised Learning in Python

Machine Learning with Tree-Based Models in Python

Deep Learning in Python

Network Analysis in Python (Part 1)

Statement of accomplishment

Ready To Learn

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Courses

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Instructors

Data Scientist with Python

Introduction to Python

Intermediate Python for Data Science

Python Data Science Toolbox (Part 1)

Python Data Science Toolbox (Part 2)

Importing Data in Python (Part 1)

Importing Data in Python (Part 2)

Cleaning Data in Python

pandas Foundations

Manipulating DataFrames with pandas

Merging DataFrames with pandas

Analyzing Police Activity with pandas

Intro to SQL for Data Science

Introduction to Relational Databases in SQL

Introduction to Data Visualization with Python

Interactive Data Visualization with Bokeh

Statistical Thinking in Python (Part 1)

Statistical Thinking in Python (Part 2)

Joining Data in SQL

Introduction to Shell for Data Science

Conda Essentials

Supervised Learning with scikit-learn

Machine Learning with the Experts: School Budgets

Unsupervised Learning in Python

Machine Learning with Tree-Based Models in Python

Deep Learning in Python

Network Analysis in Python (Part 1)

Statement of accomplishment

Ready To Learn