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R Programming

Learn about fundamental data types, logic, and how to create your own functions using the R language.

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Importing & Cleaning Data

with R

Learn how to parse data in any format. Whether it's flat files, statistical software, databases, or web data, you'll learn to handle it all.

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Data Manipulation

with R

Master advanced concepts in data manipulation using powerful tools like dplyr and data.table to make your data science projects faster and more readable.

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Python Programming

Discover important data structures like dictionaries and DataFrames, visualize real word data with matplotlib, and learn the art of writing your own Python functions.

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Importing & Cleaning Data

with Python

Learn to import data from various sources, such as Excel, SQL, SAS, and right from the web. From there, learn to efficiently prepare and clean your data so it is ready to by analyzed.

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Data Manipulation

with Python

Harness the power of tools such as pandas and SQLAlchemy so you can extract, filter, and transform your data quickly and efficiently.

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Statistics

with R

Learn key statistical concepts and techniques like exploratory data analysis, correlation, regression, and inference.

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Data Visualization

with R

Communicate the most important features of your data by creating beautiful visualizations using ggplot2 and base R graphics.

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Time Series

with R

Time series are all around us, from server logs to high-frequency financial data. Learn the core techniques necessary to extract meaningful insights from time series data.

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Applied Finance

with R

Apply your R skills to financial data, including bond valuation, financial trading, and portfolio analysis.

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Finance Basics

with R

If you are just starting to learn about finance and are new to R, this is the right track to kick things off! In this track, you will learn the basics of R and apply your new knowledge directly to finance examples, start manipulating your first (financial) time series, and learn how to pull financial data from local files as well as from internet sources.

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Machine Learning

with R

Learn the basics of prediction using machine learning. This track covers predicting categorical and numeric responses via classification and regression, and discovering the hidden structure of datasets (unsupervised learning). Learn how to process data for modeling, how to train your models, how to visualize your models and assess their performance, and how to tune their parameters for better performance.

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Machine Learning

with Python

Machine learning is changing the world and if you want to be a part of the ML revolution, this is a great place to start! In this track, you’ll learn the fundamental concepts in Machine Learning. You’ll learn all about the arts of prediction and pattern recognition; you’ll dive into a real-world case study; to wrap it all up, you’ll learn all about Deep Learning in Python.

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Track badge

Python Programming

Discover important data structures like dictionaries and DataFrames, visualize real word data with matplotlib, and learn the art of writing your own Python functions.

Learn More

Track badge

Importing & Cleaning Data

with Python

Learn to import data from various sources, such as Excel, SQL, SAS, and right from the web. From there, learn to efficiently prepare and clean your data so it is ready to by analyzed.

Learn More

Track badge

Data Manipulation

with Python

Harness the power of tools such as pandas and SQLAlchemy so you can extract, filter, and transform your data quickly and efficiently.

Learn More

Track badge

Machine Learning

with Python

Machine learning is changing the world and if you want to be a part of the ML revolution, this is a great place to start! In this track, you’ll learn the fundamental concepts in Machine Learning. You’ll learn all about the arts of prediction and pattern recognition; you’ll dive into a real-world case study; to wrap it all up, you’ll learn all about Deep Learning in Python.

Learn More

Track badge

R Programming

Learn about fundamental data types, logic, and how to create your own functions using the R language.

Learn More

Track badge

Importing & Cleaning Data

with R

Learn how to parse data in any format. Whether it's flat files, statistical software, databases, or web data, you'll learn to handle it all.

Learn More

Track badge

Data Manipulation

with R

Master advanced concepts in data manipulation using powerful tools like dplyr and data.table to make your data science projects faster and more readable.

Learn More

Track badge

Statistics

with R

Learn key statistical concepts and techniques like exploratory data analysis, correlation, regression, and inference.

Learn More

Track badge

Data Visualization

with R

Communicate the most important features of your data by creating beautiful visualizations using ggplot2 and base R graphics.

Learn More

Track badge

Time Series

with R

Time series are all around us, from server logs to high-frequency financial data. Learn the core techniques necessary to extract meaningful insights from time series data.

Learn More

Track badge

Applied Finance

with R

Apply your R skills to financial data, including bond valuation, financial trading, and portfolio analysis.

Learn More

Track badge

Finance Basics

with R

If you are just starting to learn about finance and are new to R, this is the right track to kick things off! In this track, you will learn the basics of R and apply your new knowledge directly to finance examples, start manipulating your first (financial) time series, and learn how to pull financial data from local files as well as from internet sources.

Learn More

Track badge

Machine Learning

with R

Learn the basics of prediction using machine learning. This track covers predicting categorical and numeric responses via classification and regression, and discovering the hidden structure of datasets (unsupervised learning). Learn how to process data for modeling, how to train your models, how to visualize your models and assess their performance, and how to tune their parameters for better performance.

Learn More

  • Learn real world skills

    In every DataCamp exercise, you are writing and running real R, Python, or SQL code. You won’t just learn the theory, you’ll get hands-on experience exploring real data sets in courses covering the entire data science workflow.

    Learn skills
  • A curriculum by world-class Instructors

    DataCamp courses are taught by the best instructors in the world. Our instructors come from academia and industry, are package creators and project maintainers, and have developed some of the most widely used data science tools in the world. With DataCamp, you’ll be learning from the experts.

  • Get fluent with case studies and practice mode

    Everyone knows practice is key. With case studies built into every course, you’ll get to apply your new skills right away. Plus, in practice mode, you’ll be able to keep your skills razor sharp with fun daily challenges.

    Practice mode
DataCamp was essential for getting my job, which was my break into data science.
Jamen Long used the skills he learned at DataCamp to land a full time job as a data scientist.
Jamen Louis Ofentswe Godefroy Image17

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Frequently Asked Questions

What's the difference between a career track and a skill track?

Our career tracks cover everything you need to kickstart your career, from our intro courses to our most advanced offerings. Our skill tracks are shorter and let you specialize in a specific area, like data visualization or statistics.

Once I've started, can I change tracks?

Of course! If you decide to rejoin a track, any new course progress will be applied automatically.

Will I earn a certificate for completing a track?

Yes. In addition to earning certificates for each course you complete, you will earn a special certificate upon completing a track.

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