It is not uncommon for aspiring techies to look for a Data Science certificate as a way to enter – or advance – in this ever-growing industry. Unfortunately, this is nowhere near as straightforward or as transparent a process as many initially assume, as the field is rife with career traps, and the available guides are few and not always reliable.

This article was created to provide a compass for all those aspiring techies who feel lost in the woods. I will not only guide you to the most reliable and professional providers of certificates in Data Science, but also equip you with all the insider information necessary to make an informed choice.

If you simply run after the first piece of paper you come across, you risk doing more harm than good to your professional profile. This article will make sure you find the Data Science certificate that serves your career and your future – and that gets you out of those woods definitively.

CONTENTS

What exactly is a certificate, and which are valid for Data Science?

• Is there a difference between a certificate and a certification?
• Data Science certificate vs University degree: what are the differences?
• Data Science certificate vs Data Science bootcamp: what are the differences?

How to choose a Data Science certificate

• Data Science certificates for beginners
  • Career Focus: Are Data Science certificates for beginners worth it?
• Data Science certificates for professionals
  • Career Focus: Are Data Science certificates for professionals worth it?

The career trap of Data Science certificates – and how to avoid it

So, why get a Data Science certificate?

What exactly is a certificate, and which are valid for Data Science?

A certificate is any document from a recognized authority stating that you possess a certain set of skills or experience in a given field. Technically this definition should include something like a university degree or a diploma; in reality, a ‘professional certificate’ refers to something different.

Unlike degrees and diplomas, professional certificates do not have classes, lessons or professors. Instead, you obtain them by taking the relevant exam by yourself, and you will prepare for that exam mostly independently, perhaps assisted by some pre-recorded lessons or digital materials.

Certificates are also, for the most part, relatively short-term engagements. Most are designed to be prepared for and completed in a few months – not the four or five years that a university program takes.

In the field of Data Science, certificates are many and highly diverse, ranging from simple programs for the absolute beginner to specialized ones for the advanced professionals. It therefore shouldn’t surprise you, once we start exploring the options, to find a few exceptions to the above two rules!

Is there a difference between a certificate and a certification?

Semantically, the word ‘certification’ typically refers to something a bit more advanced and difficult to attain than a ‘certificate’. In practice, though, the two terms are interchangeable synonyms, and nobody will care which of these two words you have in your CV. Don’t waste your time worrying about something so unimportant.

Data Science certificate vs University degree: what are the differences?

A professional certificate should never be conflated with a university qualification like a degree, a Masters or a PhD – even if, as mentioned above, these things can of course also be called ‘certificates’.

The main differences between the two are duration, structure and value, with university qualifications being taught programs that take several years to attain, while most certificates are independently-prepared programs to be completed in months (or even weeks).

Regarding value, let me be clear – only the more advanced and prestigious certificates on this list will be comparable on your CV to a Bachelors degree or a Masters in Data Science, and those require several years of experience in the field to be obtained. If you think an intermediate certificate can work as an alternative or a ‘shortcut’, then you’ll be disappointed. There are no shortcuts.

A common source of confusion are so-called ‘community college certificates’. This is an expression referring to short professional specialization courses awarded by academic institutions exclusively in America (similar programs exist outside of the USA, of course, but they go by different names).

Again, let me be clear: while the skills you can learn from a community college (or equivalent) course in Data Science have value, a community college certificate does not, or at least not by itself. These programs are generally designed to prepare people for work in sectors like plumbing, construction, nursing, or automotive repairs. For people looking to work in tech – beginners and veterans alike – there are much better options out there.

Data Science certificate vs Data Science bootcamp: what are the differences?

Yet another category that should not be confused with professional certificates is that of modern coding bootcamps in Data Science, even though these offer completion certificates of their own.

The main difference is that coding bootcamps are about learning new skills, while certificates are about validating skills one already has. A bootcamp will provide a taught program with an instructor and often a cohort of staff (career services, community managers) to attend to you. It will also be a high-intensity affair, in which you’ll be pushed to your limit in terms of how much and how quickly you can learn. Certificates have little support and can be taken at your own pace.

A completed bootcamp is a much superior career option for those looking to break into (or redeploy within) the world of Data Science, while a certificate is preferable for advanced professionals who wish to demonstrate proficiency with specific tools. Understand which group you belong to before committing to either option.

How to choose a Data Science certificate

In this part of the article I will list all of the most prominent certificates in Data Science, along with details and a short description of each.

As I touched on above, there are very many such certificates, some very different from each other in nature. For this reason, I have subdivided this list into the following categories.

Firstly, we will look at certificates that are appropriate for beginners, and this section will in turn be split between certs by educational providers, and those provided by major tech companies.

Secondly, we will consider certificates for professionals, which in turn will be split between certs that demonstrate general mastery of Data Science, and those that validate specialised skills, or proficiency with specific tools.

At the end of each of these parts I will include a Career Focus section to evaluate the usefulness of these different types of certifications, and what you can expect to get out of them. Do NOT choose a certificate without reading the guide to its career value. Not only do you risk wasting your time, you may actually make your CV less attractive to employers!

The only certificates I decided not to account for in this guide are those offered by academic institutions, such as Columbia University’s Certification of Professional Achievement in Data Sciences. While there is a growing number of these ‘mini-degrees’ offered in tech, they remain very closely anchored to the academic world and I don’t believe they truly belong with those discussed in this article. 

Finally, note that the prices and fees provided in this article are, in almost all cases, variable depending on the international region, and may not correspond for all applicants to the figure I have reported.

Data Science certificates for beginners

This is a compact list of all the major Data Science certificates for beginners, along with their providers and their prices. Click on each provider to be taken to the full description of their certificates.

i. Self-learning course completion certificates

The following are providers of self-learning programs in Data Science which offer a certificate on completion. These are apt for the complete beginner who wishes to introduce themselves to the world of Data Science and find out if it is something they will like. They are absolutely not in the same league as more advanced professional certificates (see the Career Focus section below), but they do demonstrate completion of the pertinent classes.

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ii. Proprietary basic skills certificates

These certificates are something like a compromise between the self-learning courses in the previous sections, and the independently prepared advanced certificates which we will consider later. They will offer some learning material and/or support, but usually this is fairly limited. The material is quite beginner-friendly, and is often meant as a stepping stone towards more advanced certificates. They are provided by major tech companies, often working in cooperation with online educational providers.

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Career Focus: Are Data Science certificates for beginners worth it?

If you are thinking of using any of the self-learning certificates listed above to find a job in Data Science, then let me dispel that notion for you right away – a certificate of completion by FreeCodeCamp or CodeCademy is an utterly worthless thing to have on your CV. Some employers may even see them as red flags, interpreting them as an indication that the applicant has nothing else to show for themselves.

The proprietary certificates, while a little better at demonstrating specific skills, are also not sufficient by themselves to find a job in Data Science. You will want the advanced certificates (see below), and the basic ones essentially just serve for you to test whether you have the foundational knowledge to start preparing for those. 

This is not to say that getting these certificates is a waste of time. But if you think you need them on your CV, then you are fundamentally misunderstanding their purpose. They exist primarily as tools for beginners and self-learners. What you get out of them is not the certificate itself, but the knowledge that you acquired when preparing yourself to get it.

A much more appropriate way to use these certificates is to apply the knowledge you learned to get them and build something for your portfolio. A good portfolio will always constitute your best certification, and that’s what will get you a job.

Data Science certificates for professionals

This is a compact list of all the major Data Science certificates for professionals, along with their providers and their prices. Click on each provider to be taken to the full description of their certificates.

iii. Generalist Data Science certificates

All of the certificates listed from here on out are obtained by signing up for an exam and then preparing for it at your own pace, which is why I no longer specify how long it takes to get one. This first part looks at certificates that validate broad, general skills in Data Science as a whole.

iv. Specialist Data Science certificates

While cloud computing qualifies as a distinct field in its own right, in practice all serious Data Science professionals will be expected to know the ins and outs of it to some extent, and a certification in this field will be among the most valuable for anyone working with data. In fact, if your portfolio already demonstrates Data Science proficiency, a complementary certificate in cloud computing may even be preferable to a general one of those above. This list also includes certificates in Machine Learning and AI. 

Career Focus: Are Data Science certificates for professionals worth it?

The specialized certificates I listed above can be powerful tools to boost your career, but they are not for everyone.

Firstly, understand that these programs are designed for people who already have professional proficiency in Data Science at a minimum. They exist for such people to demonstrate aptitude – sometimes with a particular tool or specialization – and also to sharpen or update their skills with them. 

Beginners or relatively inexperienced professionals in the field of Data Science should therefore steer clear of these. They will waste their time and money, learn very little, and only end up greatly frustrated.

Instead, the classic profile of someone who can make the most of such a certificate is that of a university postgraduate with a background related to Data Science who wishes to transfer from academia to the business world, or an established professional with a history of working with AI who wishes to switch to cloud computing.

As long as these advanced certificates are seen as complementary to one’s foundational qualifications and portfolio in Data Science – and not as their replacement – they can be a valuable tool to distinguish your CV from a host of other similar ones. Indeed, they could make the difference between a call for an interview or a rejection, or even between a salary offer of €40K yearly or one of €50K yearly.

Just make sure that your certificate matches the type of jobs you are going to apply for. An advanced certificate will boost your CV only if it is directly pertinent to the field you are applying for. Certifying that you are a beast with Python libraries when your desired position involves working with R is really not going to add much to your application.

The career trap of Data Science certificates – and how to avoid it

Most people looking for a Data Science certificate want “the one” that will impress recruiters the most and get them the job. Here’s something you should know right off the bat: such a thing does not exist.

You are either a beginner-veering-towards-intermediate, and then the only point of getting certificates is what you learn in the process – the ‘badge’ itself isn’t worth anything. Or else you are an intermediate-veering-towards-veteran, and then the certificate only gives you an edge if it complements a rich portfolio of projects.

You fall into the career trap any time that you put the pursuit of certificates above that of your skills or your portfolio (and this goes double for freelancers, for whom a portfolio is a very big deal).

Think of it this way, what’s the farthest that a certificate can get you? To a technical interview, of course. And a technical interview will also feature at least one senior Data Scientist from your prospective team.

That person is going to drill into you hard to find out exactly what you know and what you don’t. And then no certificate in the world is going to make a difference. The only things that will matter are your knowledge and your skills, which is why those should always be your priority when preparing for any job.

So, is a Data Science certificate worth it?

Data Science certificates are primarily valuable as tools to structure your own learning and pick up on concepts you do not yet fully grasp, or as marks of distinction to elevate an already strong CV and portfolio, or else – and this may be their best application – to demonstrate that you possess very specific, specialistic skills in addition to your more general ones. However, they are not an end in themselves, and are very rarely self-sufficient to get you a job.

In other words, figure out your objectives first, and then get a certificate – not the other way round. If you want to learn, go for a free course, and use the certs to signpost your progress (although there are faster and more efficient options out there). If you want to get a job, find out exactly what skills you need for your line of work first (analytics, machine learning, cloud computing?), and then get the corresponding certificate.

A certificate should offer you a variety of benefits. Always make sure those are more than just a line on your resumé.