Our Guide to Data Science Certificate Programs

What is data science?

When the researchers at McKinsey forecast the continuing proliferation of data-driven decision making, they’re touching on two disciplines — data science and data analytics — that overlap sufficiently to create confusion. Understanding the difference between the two is crucial to understanding whether a data science certificate program is right for you.

Data analytics concerns the tools and techniques surrounding the process of data analysis. Often, but not always, data analytics professionals will use existing tools and techniques on existing databases.

Data science, on the other hand, concerns the development and deployment of new tools and techniques and new ways to gather data for analysis. The analytics involved in data science will thus likely be more advanced and will frequently involve machine learning, a form of artificial intelligence. Oftentimes, data analysts and other data analytics professionals will employ methods and tools developed by data scientists.

In general, data analytics certificate programs will require fewer prerequisites and have less advanced curricula. Accordingly, they will be better for those who have less experience with programming and applied mathematics. If you are interested in learning more, check out our guide to data analytics certificate programs.

What skills are taught in data science certificate programs?

The depth of a data science certificate program’s curriculum will vary depending on the length, intensity, and overall purpose of the program, but participants can generally expect to cover the following:

• Fundamental computer science skills, including SQL, Python, and/or R programming languages

• Statistical modeling, including regression analysis

• Machine learning basics, including elementary algorithms and machine learning libraries like PyTorch and Pandas

• Advanced techniques such as deep learning and big data mining

• Data visualization techniques, often using Tableau

In addition to these skills, many data science certificate programs also include:

• A capstone project

• One-on-one mentoring and career advice

Data Science Certificate Program vs. Data Science Bootcamp?

The way we see it, all bootcamps are certificate programs — students who successfully complete one are awarded a certificate — but not all certificate programs are bootcamps. In general, you can expect non-bootcamp certificate programs to distinguish themselves by being:

Shorter: While data science bootcamps can entail three or more months of 20+ hours of instruction per week, a non-bootcamp data science certificate program will generally be shorter, if not in the total length of the program, then at least in the amount of time devoted to learning each week

Less intensive: As would be expected with a reduced run-time, a non-bootcamp data science certificate program will often not dive as deeply into the material as a data science bootcamp would.

Less expensive: As would be expected with a reduced run-time and intensity, a non-bootcamp data science certificate program generally won’t be as costly as a bootcamp, with tuition often running in the hundreds and thousands of dollars, not the tens of thousands you would expect with a bootcamp.

Geared to different audiences: While aspiring data scientists might flock to bootcamps hoping mostly to gain the skills necessary to land an entry-level job as a data scientist or data analyst, the motivations of those participating in non-bootcamp certificate programs are more varied, as we will see in the next section. While the curricula of most data science bootcamps are generally quite similar, the curricula of non-bootcamp data science certificate programs vary according to who exactly the target audience or audiences are. Data science certificate programs also might not offer the extensive career services that data science bootcamps offer.

If the intensity of a bootcamp and the prospect of landing an entry-level job warrants the cost for you, head over to our online data science bootcamp guide to see our top picks.

What are some use cases for data science certificate programs?

As audiences differ, so too do the use cases for non-bootcamp data science certificate programs. While McKinsey is likely right that all professionals will engage in data-driven activities by 2025, there is nevertheless significant variation in how they will do so. This, together with differences in where potential participants in their careers, means that non-bootcamp certificate programs are designed with several utilities in mind.

Exploring a career in data science

Due to their relative affordability and lower time commitment, non-bootcamp certificate programs are a great option for those who are data sci-curious but not ready to take the plunge with a more expensive and time-intensive bootcamp or data science master’s program. While a certificate program might not always make you job-ready — it almost certainly won’t let you jump into a senior data scientist role — it will generally offer high-level exposure to the fundamental concepts and skill of data scientist and the day-to-day existence, so you can prototype a potential data science career path in a risk-free environment. 

Adding a skill set to boost job performance

Non-bootcamp certificate programs are also great options for those already working as a data analyst, in business intelligence, business analytics, or computer engineering — or even far-off fields like social work, supply chain management, retail — who aren’t able to sacrifice the time to take a bootcamp or go to graduate school, but could benefit by adding data science skills like machine learning and deep learning, applied statistics, and data management.

Managing teams of data scientists

Non-bootcamp data science certificate programs are also a great way for a manager or executive to learn more about the discipline. While some aspects, like capstone projects, might be less relevant, learning the basic vocabulary, processes, and possible outcomes of data science is indispensable for those who need to manage a team of data scientists, expand their company’s data operations, or perform a cost-benefit analysis of doing so.

What’s our approach?

Online, you can find countless sites purporting to rank the best data science certificate programs. Often, they’ll support their rankings by laying out the different criteria by which they evaluate and order the programs they feature, separating the “best” from the “rest.” 

But while publishing ranking methodologies does lend some objectivity to their program rankings, these sites are missing the bigger issue: ranking in the first place, identifying the “best” programs, presumes that just one kind of student is seeking certification. As the above use cases demonstrate, this is anything but the case.

For our picks, we’ve foregone ranking and focused instead on showcasing a variety of stellar programs that can meet the variety of different needs out there. Our hopes are that interested individuals will be able to find something that works for them.