DataCamp vs. Coursera

Stacey M. December 9, 2024 1834 0

DataCamp or Coursera, which is better for you? DataCamp is probably better if you want to learn data analysis or data science, whereas Coursera is better for computer science or business-related subjects. Still, both platforms offer good courses on data science and related subjects. Moreover, the pricing is almost the same (if we do not consider online degrees).

Now, let’s dive into the detailed comparison.

DataCamp and Coursera are both huge and widely known companies. Each company is good in what it offers but which one to choose? In this Datacamp vs Coursera comparison, we’ll take a closer look at both providers and what courses they have to offer–especially in relation to data science.

DataCamp vs Coursera verdict

Coursera and DataCamp are both a good choice for learning data science and generally for online learning. Your choice is completely up to you as we recommend both companies, To decide which one to go with, take a look at their curriculums, at online reviews available on Reddit and other platforms, and then make a final decision.

If your focus is on data analysis, data science, or machine learning, and you are looking for a platform with simple pricing and practical exercises, DataCamp is an excellent choice.
If you are seeking a wider range of courses, online degrees, certificates from leading universities, and flexible learning programs, Coursera is the ideal solution.

Brief Comparison

	DataCamp	Coursera
Price	$42/month if paid monthly or $27/mo if paid annually ($324/year)	free or from $49 up to $399
Total number of courses	520+ courses	7000+ courses
Programming languages	Python, R, SQL, Scala, Java, Julia	avaScript, Java, Scala, Swift, C++, Python, R, SQL and major programming languages
Specialize in	Data Science, Data Analysis, Machine Learning	Social Sciences, Business, Health, Data Analysis
Hands-on projects	yes	yes
Certificates	yes	yes
Online degrees	—	over 25

If you need more information on each e-learning platform, check out this Coursera review or DataCamp review.

DataCamp vs Coursera Similarities

Both companies have a number of programs in data science, machine learning, and other data-focused subjects.
Both have single courses and longer programs made of single courses.
Both providers have free but limited content.
Both companies offer courses for people with no prior knowledge or experience and work best for beginners.
Both provide a certificate upon completion (in paid programs).
Both providers offer hands-on projects to practice theoretical concepts.

Main Differences between DataCamp and Coursera

Coursera offers courses on a wider range of subjects (from coding to psychology), whereas DataCamp specializes in data-related subjects (data analysis, machine learning, etc)
Coursera has more types of programs including online degrees; DataCamp offers both short and long programs but there are no online degrees.
Coursera offers peer feedback as a mandatory thing to finish paid programs while with DataCamp you can get peer assessment only on their community space.
DataCamp offers completely self-paced learning while some of Coursera’s programs have deadlines and scheduled classes.
Coursera has both instructors from academia and people from businesses while DataCamp’s instructors are mainly from the business sector.
DataCamp’s content is available in English only, while Coursera has content in other languages as well (or at least with subtitles).

==>> Go to Coursera

==>> Go to DataCamp

Pros & Cons of DataCamp and Coursera

Coursera has more to offer with dozens of courses and recognized instructors. But its course structure and policy are somewhat confusing.

Pros

High-quality content
Instructors from top universities and corporations
More content is available for free
A huge number of courses

Cons

It can be confusing to understand the difference between program types and the pricing approach
Cost can get very high
Less data-related courses

Go to Coursera

DataCamp specializes in data analysis so it has more courses on data-related subjects and its pricing model is very simple. However, some courses and quizzes might be too simple to progress.

Pros

Specializing in data analysis & data science
Cost-effective and simple pricing policy
A lot of hands-on projects

Cons

Not good for middle and advanced levels
Instructors are not from well-known institutions or companies
Some content and assignments are too simple

Go to DataCamp

DataCamp vs Coursera Cost

Both companies have free content but of a different kind. Datacamp offers the introductory modules of each course for free. Then, it has an easy pricing model: you can either pay $42 per month or opt for an annual subscription, which reduces the cost to just $27 per month. Free content by Datacamp is not enough to get some skills so you’ll need to go for a paid subscription.

Coursera’s pricing model is more complicated as it has more options. It has completely free courses where you can access its content fully but with no certificate after completion. Meanwhile, there are a lot of other options. It includes Specializations and Professional Certificates with the cost starting at $39/mo, MasterTrack® Certificates from $2,000 and even online degrees from $9,500.

	DataCamp	Coursera
Free plans	yes (first module of each course)	yes (full course without a certificate)
Monthly price	$42/mo	$49/mo
Cost per year	$324/year	from $399/year

DataCamp vs Coursera Courses

DataCamp has short single courses and two types of longer programs (skill tracks and career tracks) for those looking to study data science and improve their qualification. It has over 520 courses in total and all of them are focused on data skills. The majority of them are centered around either Python or R.

The best way to get data science skills is to go for a career or skill track as these are sets of subject-related courses. You can take a single course if you want to get a specific skill or just understand whether data science is good for you.

After completing DataCamp’s courses, you can take an exam to earn a DataCamp Certification, which allows users to demonstrate their expertise and preparedness for professional roles. The qualification test is included in the premium membership and allows flexibility in scheduling the exams. Please note that Career and Technology Certifications are valid for two years.

As part of its services, DataCamp also offers DataLab, a tool that allows users without any technical skills to transform raw information into actionable insights.

DataLab supports connections not only to files, databases, and popular data warehouses, but also to various data sources. It leverages your interaction history and organizational context to enhance analysis quality. When you buy a premium subscription to this DataLab tool, it gives you unlimited access to the AI Assistant, advanced version history and better computational resources features.

Designed for personal use as well as teamwork, DataLab has made it simple for any employee to collaborate in understanding organizational data. The free tier enables the user to develop 3 workbooks and make 20 AI Assistant queries.

Coursera has a huge number of programs on topics from different domains–a lot more compared to DataCamp. It has over 7000 courses in total with short (single courses and Guided Projects) and long programs (Specializations, Professional Certificates, MasterTrack® Certificates, and Degrees) on this list. Moreover, Coursera has over 3000 programs related to data science (in different languages).

The most data-related content is available within Coursera Specializations. The most serious approach would be to choose an online degree but it’s also a very pricey option.

So, let’s be more specific and compare the most popular courses by Datacamp and Coursera related to data science.

Data Scientist with Python on Datacamp

This course is based on learning Python skills as the main programming language for data science. It covers the foundation of Python and more advanced topics like Machine Learning. A huge part takes Pandas and Numpy to tackle such tasks as data cleaning and data manipulation. Another huge part of it is Machine Learning and scikit-learn package that helps with these tasks. There would also be tasks where you’d need to deal with building a predictive model and run hypothesis testing.

In a nutshell, the course covers the main topics needed for data science. It teaches solid Python skills but misses the basic math content needed for to work in this domain. Thus, it would be best if you have a background or a higher education to have solid math and statistical skills.

Python
Libraries: pandas, NumPy, Matplotlib, etc.
Beginner friendly
90 hours
23 courses
11 projects
3 skill assessments
Price: $13/mo

==>> Datacamp’s main alternative: Data Scientist with R

IBM Data Science Professional Certificate on Coursera

The program is an all-in-one course for learning Data Science. It uses Python and its libraries (NumPy, Pandas, Matplotlib, Seaborn, Scipy) as the focus programming language and includes hands-on practice in the IBM Cloud utilizing real-world data sets. One of the main modules here is Data Analysis with Python where you would learn data analysis, data wrangling, and model creation.

Moreover, there is the machine learning module that touches the topic but without going deep into the subject.

There are also topics on SQL and databases.

This program also includes a dedicated section on the Data Scientist Career Guide, which provides guides for interview preparation and creating a professional resume. This approach simplifies the process of finding and getting the first job for students who have completed their studies.

All in all, the course is good and gives a solid understanding of Data Science. However, it also doesn’t cover math fundamentals and is light on statistics that are needed for working in this field. Thus, you should already have the understanding or learn these subjects additionally.

Python
12 courses
11 months to complete (4 hours/week)
$49/mo
Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, and more
Projects: predict housing prices, extracting and graphing financial data, querying census and crime data, applying machine learning to predict loan repayments, creating dashboard for flight reliability

==>> Coursera’s main alternative: Data Science Specialization by The Johns Hopkins University

Here are other Machine Learning programs on Coursera and Datacamp you can compare yourself. They are also recommended by our team.

Machine Learning Specialization on Coursera

Python (NumPy and scikit-learn), TensorFlow
3 courses
Instructor: Andrew Ng (top instructor)
2 months to complete (10 hours/week)

Courses included:

Supervised Machine Learning: Regression and Classification
Advanced Learning Algorithms
Unsupervised Learning, Recommenders, Reinforcement Learning

Machine Learning Scientist on Datacamp

Python (PyTorch, Spark and Keras, scikit-learn), TensorFlow
85 hours
21 Courses
1 Skill Assessment

Courses:

Supervised Learning with scikit-learn
Linear Classifiers in Python
Machine Learning with Tree-Based Models in Python
Extreme Gradient Boosting with XGBoost
Cluster Analysis in Python
Natural Language Processing with spaCy
Machine Learning with PySpark
etc.

DataCamp vs Coursera Courses for Business

When selecting a platform to upskill your team, the choice often comes down to specific business needs. DataCamp and Coursera for Business pay attention to distinct learning priorities: DataCamp focuses on fostering technical proficiency in data and AI, while Coursera offers a broader, multidisciplinary approach to skill-building. Below is a detailed comparison to help you choose the right fit for your organization.

1. Scope of Learning and Skill Development

DataCamp for Business provides more than 500 courses that focus on developing data- and AI-related skills. It specializes in hands-on, active learning for topics such as Python, SQL, R, and generative AI; this way, a team can quickly use its learning against a real-world scenario. On the other hand, Coursera for Business is a wide learning platform covering leadership, business strategy, and technical skills for diverse teams. Coursera also has guided learning paths, making it the best choice for teams with diverse skill requirements and different business types.

2. Customization and Team Support

Both platforms offer learning pathways that may be customized, but their mechanics differ.

DataCamp provides its in-browser IDE (Workspace) courses in a package for targeted learning that is customized, data-centric, and personalized. Their technology is scalable for any business from 2 to over 10,000 users.

On the other hand, Coursera merges the Skills Dashboard, with which businesses can track team progress and specific skills development. While Coursera is much better in providing global content in 54+ languages worldwide, DataCamp emphasizes active data-driven learning with a smaller set of highly specialized courses.

3. Certifications and Credentials

The DataCamp certification program is well-acknowledged and globally recognized, particularly in the areas related to data and artificial intelligence. Moreover, employees can validate their actual capabilities with industry-recognized certifications, thus enhancing credibility for teams and enabling ROI of the company.

Meanwhile, Coursera offers talent pathways to globally recognized credentials such as professional certificates — even degrees — for employees to motivate and develop in their careers. Thus, Coursera becomes the best choice for all organizations with emphasis on long-term employee development across various domains.

Pricing and Features Comparison: DataCamp vs. Coursera for Business

Feature	Coursera for Business	DataCamp for Business
Plans Available	For 5-125 users: $399/user/year	Teams: $27/user/month (billed annually)
	For 125+ users: Custom pricing	Enterprise: Custom pricing
Free Trial/Guarantee	14-day money-back guarantee	No free trial; free plan for educators
Catalog	8,400+ courses from top universities and companies	520+ courses focused on data and AI
Credentials	140+ professional certificates and degrees	Recognized certifications in data and AI
Analytics and Reporting	Detailed dashboards to track skills	Advanced analytics and LMS/LXP integration
Integration Options	Single sign-on (SSO), API, partner integrations	SSO through Okta, Auth0, Azure, and more

Instructors

As Coursera has a huge number of courses, it has also a long list of instructors. Many of them come from well-known institutions like Stanford, Yale, or Princeton University; all in all, there are many instructors from academia. Meanwhile, there are also instructors from the business sector, including tech giants like Google or IBM.

Most of DataCamp’s instructors are mainly from the commercial field, usually working for less-known companies. Moreover, there is no affiliation between DataCamp’s courses and universities.

Both Coursera and DataCamp allow has separate pages with instructors’ bio and social media links so you can always get more information before deciding on the course.

Learning Style

DataCamp offers a fully self-paced learning experience–you can start and continue anytime. While DataCamp has a recommended timeline, there are no deadlines. Moreover, you are billed for a year, so there’s no rush to finish a course quickly but there’s also an option to pay monthly if that suits you better.

Coursera also promotes itself as a platform for self-paced learning; however, it has a more complicated approach than DataCamp. Coursera course has a recommended deadline but missing it doesn’t affect your grade in most courses as well as the ability to get a certificate. A missed deadline can just result in you not getting peer reviews. However, when it comes to Coursera’s degrees, there are strict deadlines that have to be followed.