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Get Ready for Data Science at Columbia University

Hoping to study data science at Columbia University? DataCamp can help you build your data skills across a range of disciplines.

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  • Practice and apply your skills

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Popular Courses for Columbia University Students

Introduction to Data Science in Python

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

Clock4 hours
Hillary Green-Lerman Headshot

Hillary Green-Lerman

Lead Data Scientist, Looker

Introduction to Statistics in R

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

Clock4 hours
Maggie Matsui Headshot

Maggie Matsui

Curriculum Manager at DataCamp

Introduction to Statistics

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

Clock4 hours
George Boorman Headshot

George Boorman

Core Curriculum Manager, DataCamp

Intermediate Python

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

Clock4 hours
Hugo Bowne-Anderson Headshot

Hugo Bowne-Anderson

Data Scientist at DataCamp

Introduction to Linear Modeling in Python

Explore the concepts and applications of linear models with python and build models to describe, predict, and extract insight from data patterns.

Clock4 hours
Jason Vestuto Headshot

Jason Vestuto

Data Scientist, University of Texas at Austin

Machine Learning for Everyone

An introduction to machine learning with no coding involved.

Clock2 hours
Hadrien Lacroix Headshot

Hadrien Lacroix

Curriculum Manager at DataCamp

Prepare to Study Data Science at Columbia

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Columbia University follows a multidisciplinary approach to its data science course, incorporating in-depth teaching of concepts in Machine learning, R, and Python. 

With recent reports suggesting an acceptance rate of 3.73% for the class of 2026, it has become one of the most challenging universities to seek admission to. 

Needless to say, the correct preparation can definitely boost your chances. With the guidance of our data evangelists on courses perfectly curated for your specific needs, you can acquire the skills necessary to achieve a place at your dream college. With DataCamp,  you can do the following:

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Practice your Data Skills

Practice makes perfect! At DataCamp, you can attempt our byte-sized challenges after each course to test your newly learned skills. Complementing the in-course challenges, DataCamp Projects allows you to execute your acquired abilities in a real-life setting using real-life tools. 

Under this umbrella term, there are two separate categories: Guided Projects which provide users with a follow-along guidance approach towards real-life tasks and tests; and Unguided Projects which are perfect for intermediate and advanced students to demonstrate their learning in a more open-ended data science problem.

Work with Real Datasets

With our Workspace Datasets, put your newly acquired skills to the test by dealing with real-world problems. Analyze the data sets from your field of interest in a more applied setting with our end-to-end projects. Champion your abilities from a collection of real-world datasets, including tech data (such as tech stock prices), entertainment data (such as online ticket sales) and health data (such as rates of disease cases).

Gain Sharable Statements of Accomplishments

Every course you complete on DataCamp is rewarded with a shareable Statement of Accomplishment. These can be shared with your network or as part of your Columbia University data science application to show your progress in various subject areas.

As Columbia data science applicants, our data scientist certificates can help you fast-track your data science skills. You can equip yourself with the necessary skills essential to your degree and demonstrate the knowledge you’ve learned along the way.

Compile Your Own Portfolio

Create your own portfolio of projects and gain insights from fellow students on our DataCamp Workspace, a cloud-based collaborative platform where you can share, envision and analyze your data science work. With built-in datasets and accessible templates, you can take your skills to the next level in no time.

Columbia Data Science FAQs

Does Columbia have a data science master’s?

Columbia University prides itself on its highly sought-after Masters of Science in Data Science. To be eligible for this program, the student must have an undergraduate degree and a thorough understanding of higher-level calculus, linear algebra, and foundational computer programming.

Is Columbia’s applied data science program worth it?

Masters of Science in Applied Analytics is a well-rounded program that provides the perfect blend of leadership and data analytical skills. To students aspiring to widen their business acumen, this program can certainly enhance your management and strategic decision-making. It is delivered by leading scholars in their field.

What skills do I need before enrolling in a data science course at Columbia?

There isn’t any form of prior computing experience necessary for undergraduate courses at Columbia University. The pre-introductory courses are designed to deliver the foundational computing knowledge for the upcoming modules. However, the aspiring master's students must have sufficient prior knowledge of fundamental quantitative course material and basic exposure to computer programming.

What are the Columbia entry requirements?

Columbia University expects its aspiring students to attempt either the SAT or the ACT (excluding the writing section). If you do not qualify for Columbia University’s English Proficiency requirements, you must attempt one of the following: 

  • TOEFL (Test of English as a Foreign Language) - Minimum score of 105 is necessary 
  • IELTS (International English Language Systems) - Minimum score of 7.5 is necessary 
  • DET (Duolingo English Test) - Minimum score of 125 is necessary

What is the Columbia acceptance rate?

Based on the Columbia College article, the university is highly competitive with an acceptance rate of just 3.73%. It received a total of 60,377 applications, with only 2,253 admitted into the class of 2026.

How can I get into Columbia?

Given the prestigious status of the university, students must excel in the standardized tests to stand a chance. Along with academic accomplishments, the university aims to enroll students with holistic personalities, exhibiting unique and diverse extracurricular and intellectual interests. A varied portfolio of work can also help.

Can DataCamp support my studies at Columbia?

DataCamp is an extremely intricately designed online platform for upscaling your data science skills. With its user-friendly interface, it could certainly complement the learnings at an undergraduate degree level by giving you more direct applications of your newly acquired skills.

Ready to learn?

With our online learning platform, you take an array of courses across different competency levels, all at your own pace. If you’re preparing for your data science journey at Columbia, DataCamp is here to help.

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