DataCamp vs. Coursera
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.
Brief Comparison
| DataCamp | Coursera | |
| Price | free or $25/mo $300/year | free or from $39 (per single course) up to $9,000 |
| Total number of courses | 390+ courses | 7000+ courses |
| Programming languages | Python, R, SQL, Scala | Python, R, SQL and major programming languages |
| Specialize in | Data Science, Data Analysis | Social Sciences, Business, 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).
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.
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.
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’ll need to pay $25/month but with the only option of an annual payment. 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 $9,000.
| DataCamp | Coursera | |
| Free plans | yes (first module of each course) | yes (full course without a certificate) |
| Monthly price | $25/mo | $39/mo |
| Cost per year | $300/year | from $286/year |
DataCamp vs Coursera Courses
DataCamp has short single courses and two types of longer programs (skill tracks and career tracks). It has over 390 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.
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
- 97 hours
- 25 courses
- 6 projects
- 3 skill assessments
- Price: $12.42/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) 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.
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
- 10 courses
- 11 months to complete (4 hours/week)
- $39/mo
- Libraries: Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, and more
- Projects: random album generator, predict housing prices, best classifier model, Predicting successful rocket landing, dashboard and interactive map
==>> 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)
- 3 months to complete (9 hours/week)
Courses included:
- Supervised Machine Learning: Regression and Classification
- Advanced Learning Algorithms
- Unsupervised Learning, Recommenders, Reinforcement Learning
Machine Learning Scientist on Datacamp
- Python (Spark and Keras, scikit-learn), TensorFlow
- 93 hours
- 23 Courses
- 1 Skill Assessment
Courses:
- Supervised Learning with scikit-learn
- Linear Classifiers in Python
- Machine Learning with Tree-Based Models in Python
- etc.
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.
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.
Both companies offer high-quality content and to choose which course is better for you, you should check the curriculum and its instructor.
Among the main alternatives for learning data science are Udacity, 365 Data Science, and Dataquest.
DataCamp vs Coursera final 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.
