DataCamp vs Dataquest 2021: Which is better for data science?

Today, we'll take a look at two of the industry's heavyweights in online data science education: Dataquest and DataCamp.

These platforms are excellent resources for any data scientist at the beginner or intermediate level who is looking to advance their career. Both provide distinct learning paths based on Python, R, and SQL. They also offer a wide range of courses on topics such as machine learning, statistics, database engineering, data visualisation, and web scraping.

What will I learn?

If you're wondering whether these platforms can teach you everything you need to know about data, the short answer is probably not. Having said that, they both provide an excellent foundation for many of the skills you'll be using, implying that these tools are an excellent way to supplement content from other learning providers.

What about certificates?

If you believe that working through everything on one of these sites will immediately land you a job, you're setting yourself up for disappointment. The pair provides certifications for completing their content, but the unfortunate reality is that most employers do not value certificates obtained online. While unfortunate, this is understandable; most online learning providers lack industry accreditation, and there is usually no verification process to ensure people are who they say they are. However, Coursera and edX are making strides in providing verifiable data science certificates.

Despite their flaws, certifications are an excellent way to demonstrate your dedication to self-improvement. These platforms can also provide you with the skills and inspiration you need to create a project portfolio; your portfolio is likely to be one of the first things a potential employer will look at (not your listed skills and education). As a result, don't dismiss platforms like these as unimportant for job hunting.

Dataquest

Dataquest is an online learning platform that teaches data science to users. It offers a variety of career and skill paths, allowing you to create a learning plan that is tailored to your specific needs.

Strengths
In terms of content structure, each exercise employs a body of text to explain what the section covers. It also describes any accompanying datasets as well as the problem you'll be solving. Unlike DataCamp, there are no instructor videos to help explain concepts in greater depth. If you prefer a more independent approach to learning, skimming through content to focus on areas where you need more assistance, this platform may be for you.

One of Dataquest's key strengths is that it does not spoon-feed you solutions to more difficult problems. As a result of the lack of guidance, you must rely on other resources, such as Stack Overflow, to work your way through exercises when you become stuck. While this could be interpreted as a criticism of the platform, in reality, it is simulating the process that developers go through when working on complex problems in real life. Most experienced programmers will tell you that they don't waste time memorising complicated syntax and that the real skill is knowing how to quickly locate the code that you need to plug into your scripts.

Project-based education
Projects are central to the Dataquest learning experience and are integrated directly into the exercises; each course concludes with a guided project. This distinguishes Dataquest from its competitors; many online platforms offer projects. Many providers treat these as an afterthought. There is nothing compelling users to work on projects in between courses to consolidate their learning. Users must complete projects in Dataquest to mark courses as completed before moving on, requiring them to devote time to project work.

Weaknesses
A common complaint about Dataquest is that its R and SQL learning content could be better. The Python learning material is excellent, but the R and SQL material isn't up to the same standard. However, we could argue that putting Python first makes sense. Because of its versatility, it is the most useful language for a budding data scientist to learn. According to the 2020 Kaggle ML and Data Science Survey, 78 percent of data professionals surveyed use Python on a regular basis, demonstrating the importance of Python for data science. However, when asked about SQL and R, 38 percent and 21 percent of respondents, respectively, said they used these languages. The graph below depicts the complete survey results for this question. Despite Python's importance, these figures show that any learning platform aiming to be a one-stop shop for data science must have significant Python, SQL, and R offerings.

Pricing and Accreditation
The free offering accounts for roughly one-third of the total website content, with limited access to lessons, practise problems, and community features. Upgrading to a premium plan grants users full access to these areas as well as unlocking the site's projects section, which grants you access to additional projects (on top of those included in the lessons).

When it comes to pricing, Dataquest uses annual plans, which start at $588. However, they frequently offer a fantastic 50% membership discount, bringing the price down to a reasonable $294.

Dataquest provides premium members with a certificate for each course or path they complete. Premium members can also schedule one-on-one office hours with data scientists. The office hours may be far more valuable than the certificates, as you can use them to gain insight into the data science industry as well as some pro tips to help you land your dream job.

DataCamp

DataCamp, like Dataquest, is an online learning platform that teaches data skills and provides a variety of career and skill paths. On DataCamp, however, these paths are referred to as tracks.

The DataCamp user interface
DataCamp courses begin with an instructional video that explains the concepts you'll be using in the accompanying exercises. Furthermore, all DataCamp instructors are either experts in their field or master's/Ph.D. level educators. level. With such an impressive faculty on board, DataCamp could be an excellent option for you if you prefer to learn visually.

Strengths
This platform's SQL and R offerings are far more comprehensive than Dataquest's. DataCamp provides customised tracks for both of these languages, as well as a wide range of Python courses.

DataCamp also has a fun, gamified interface that rewards you with experience points for completing exercises. Unfortunately, DataCamp doesn't do much with XP other than serve as an indicator of your overall progress. You can also gain XP by completing daily practise challenges, which are useful for days when you don't have time to devote to your studies. You can finish these in 5 minutes or less whenever you have a spare 5 minutes. You can also complete challenges and courses on your phone using the DataCamp app (shown below), which Dataquest lacks.

Weaknesses
One major criticism levelled at DataCamp is that the exercises only require you to fill in the blanks. This style is advantageous because exposure to pre-written scripts can aid in learning the proper way to code. It also saves you time on coding that is unrelated to the lesson. Unfortunately, this reduces the difficulty of the exercises, which can lead to decreased content retention. Building solutions from scratch is how you'll do it in the real world, so the platform's lack of this feature is a significant limitation. To some extent, the recent addition of projects addresses this issue by allowing you to work through real-world problems, either guided or unguided. Unfortunately, unlike Dataquest, project completion is not required for course completion.

Pricing and Accreditation
You can access the first chapter of each course for free as part of the free package. You will also have limited access to practise challenges, limited project access, and unlimited access to practise assessments as part of your free membership. A standard membership grants access to all of the courses and practise challenges, as well as the data science certification exam. Users must purchase the premium membership to gain full project membership.

The pricing is slightly lower than that of Dataquest. You can purchase a standard membership for $300 or a premium membership for $400 with annual billing. They, like Dataquest, frequently offer discounts on paid memberships. For example, when I was writing this article, there was a 50% discount available, bringing the total premium price down to a very appealing $200.

DataCamp members can earn certificates of completion for any courses they've completed. They can also obtain the DataCamp data science certification after completing six timed assessments, a coding challenge, and a case study.

Conclusion

Both Dataquest and Datacamp are excellent platforms for honing your data science skills. Furthermore, they both have substantial free offerings, so if you're considering trying one out, why not work through some of the free content to see if the platform is right for you? Similarly, if you're undecided between the two, try taking a free course on each website to see which one feels like a better fit for you.

Neither of these will provide you with the knowledge you need to land your dream job or become an expert in the field, but they will help you build a stronger foundation if you are at the beginner or intermediate level. There is no substitute for experience, so begin working on projects that can be used to replace paid employment on your CV; this will greatly assist your job search.

Despite their flaws, both platforms receive high marks. Furthermore, their prices are very competitive when compared to some of the other data science courses available online, so if you invest in a paid membership for one of them, you won't be disappointed!

Which is better?

Dataquest, in my opinion, is an excellent platform for getting started with data science. I prefer text-based content; my prefered learning style is to skim through information and focus on the key points, ensuring that I retain what I need. While time-consuming, I'm content to fill in the blanks with some research in another tab for more complicated concepts. However, I believe the interface could be a little more exciting at times, as it is similar to that of some of Dataquest's free competitors, such as HackerRank. Dataquest's content is far superior, but the interface does not reflect this.

I'm a much bigger fan of DataCamp's gamified interface, even if their XP system feels a little off. I also like the wide variety of tracks (63 total vs. 16 total for Dataquest), which better caters to the learning goals of users. Despite the platform's advantages, I find it difficult to overlook their fill-in-the-blank approach. When combined with the XP system, it allows you to quickly work through problems while having fun, which means you'll soon be soaring through your chosen track. However, the point of the platform is to learn, and if you're rushing from one exercise to the next without properly thinking through the challenges, there's a good chance that much of what you're learning won't stick.

If I had to choose one of these platforms, I'd go with Dataquest's text-based content. The content isn't as enjoyable to work through as it is on DataCamp, but my goal is to learn, so I need to prioritise which platform is best for that. Finally, the decision is yours to make, and you should not take my word for it; I stand by my previous recommendation that you try both platforms before deciding which one you prefer.