Data Science - Advantages & Applications

Data science is booming, the appeal of positions in the field is eliciting unprecedented interest, and people across disciplines are trying to maneuver into the field. However, many career-changers quickly find a skills-gap they need to overcome, and even more of them don't know that even with some demonstrable competence, the job search will be a significant challenge.

I'm Josh, Sr. Admissions Manager at Metis Data Science, an immersive 12-week data science bootcamp. In this article, you can expect to learn the differences between data science bootcamps, online programs, and university programs. I'll identify some of the pros and cons of each and highlight specific criteria that make immersive data science bootcamps shine amongst the rest. I'll also outline the bootcamp application process, give you an idea of what to expect, and provide some tips on the right questions to ask when evaluating the array of bootcamps on the market.

Pros & Cons: Data Science Bootcamps vs. MOOCs vs. University Options

MOOCS Lack Structure & Career Support

Those eager to make the shift can develop the requisite proficiency a number of ways. Many start with massive open online courses (MOOCs) because the investment is low and you can study at your own pace. MOOCs are great for these reasons, but a lot of students realize they crave feedback in a structured, project-based learning environment where they can practically apply their skills. Online courses also don't offer career support.

Universities Lack Project-based Curriculum & Effective Job Placement

Students might then research traditional higher education options only to find that most universities don't offer data science degrees/concentrations, and those that do often feature programs that are more theoretical than applied, with a curriculum that can fall out-of-date fast. As for career support at universities, I've often heard from graduates that there are significant gaps in assistance and attention provided that leaves much to be desired. These things combined are what drive a lot of people to investigate bootcamps (immersive learning schools) as they attempt to re-tool for a career in the new economy.

The Data Science Bootcamp Difference

Data science bootcamps are taught by practitioners who train students on industry-relevant tools and technology so they can accelerate their careers or pivot into a new career path. Programs tend to last 12 weeks and run full-time with a mix of lecture and project-based learning. They also tend to have strong career support. At the Metis Data Science Bootcamp, where I work, for example, our careers team offers each cohort 6 workshops, ~8 guest speakers, a solid network of hundreds of data scientists, a Career Day and other career-focused events, and more.

Which Data Science Bootcamp Is The Best? The Application Process Speaks Volumes

While I believe bootcamps are a fantastic option for students ready to take the next step, not all bootcamps are created equal, and the admissions process is often quite telling. I've spent the last three years in the bootcamp admissions space and have been in touch over the years with a range of staff working at well over a dozen bootcamps. You can tell a lot about a bootcamp from its application process, and I'd love to share my expertise to help you understand more about what to look for in a bootcamp and in the application process.

Top 5 Things To Know When Researching Data Science Bootcamps

Applying to bootcamps isn't super intuitive since the space is only about six years old and the process isn't standardized like it is in traditional higher ed (where you expect to submit standardized test scores), a few references, an essay, transcripts, and maybe 1-2 other supporting documents. The spectrum of application processes ranges from bootcamps that only collect your background information and then move you to a "culture fit" interview, to much more rigorous applications that include multiple assessment rounds like at Metis. Here are the top five things to investigate as you consider bootcamps:

1. The Application Process: High Standards [Usually] = A Quality Program

Application processes vary from bootcamp to bootcamp. At coding bootcamps, some require as little as a self-assessment and video interview to determine a "cultural fit" before rendering decisions. Others want you to complete coding assessments. The more elite coding bootcamps require live-coding during video interviews. Data science bootcamps, on the other hand, tend to have more rigorous application standards because data science requires both programming and math/stats skills. Metis, for example, has perhaps the most competitive bootcamp application (check out our tool Metis Admissions Prep to discover more about the Metis application and how to prepare). First, you submit a written application completed by filling out background information, a self-assessment, and answering a few technical questions including a small challenge translating pseudo-code into Python. Then you complete a technical, time-constrained assessment on a platform called HackerRank, where you demonstrate your background in statistics, probability, linear algebra, and calculus as well as mastery of the fundamentals of Python in various exercises. You're also asked to submit a project idea.

All of this is extremely important because the strictness of an application process can make or break the quality of a program and student experience. Imagine you apply to a program with low standards. The level of commitment students possess will range widely because they will have invested so little in the application process. Your classmates' technical skill levels will also vary dramatically and everyone will be launching from different plateaus instead of a unified launchpad. As a student, you want to be sure you are working with driven, like-minded individuals with whom you can collaborate and succeed in the bootcamp (and eventually in the job search!).

2. Transparency: Ask The Right Questions

How transparent a bootcamp is matters because you are investing a substantial amount of time and money. Most bootcamps run 12 weeks, and in the coding bootcamp space, prices range from $10,000-18,000. In the data science space, prices are more likely to range from $16-17,000. On top of this, you'll need to factor in the cost of not working during a post-bootcamp job search. Here are some questions you'll want to check for on the bootcamp's website and when connecting with admissions teams:

• Can I view the curriculum?
• What is your data science bootcamp application process?
• What job titles do graduates obtain after they graduate?
• What percent of graduates found a job after they graduated and exactly what goes into that statistic? Are all graduates included? Is it independently verified and audited or does the bootcamp simply set their own standards about who counts and who doesn't?
• Who are the instructors and do they have industry experience?
• What kind of career support is offered?
• Is it an accredited bootcamp? What does that accreditation mean?

3. High Touch: Remember, You're Not Buying A Used Car

Bootcamp admissions shouldn't feel sales-y and pushy. A solid admissions contact should feel like someone you can trust, who has your best interests in mind, and who wants to help you figure out your best next step (not just the one that's best for a program's ROI). You aren't buying a car; you are shifting/upskilling into a new career path.

At Metis, I try to make myself as accessible as possible to interested potential students and the applicants with whom I work. I know they are making huge commitments and big changes in their lives and they need support and information to make the right call. Sometimes it's a 10-15 minute check-in phone call with me to ask questions about the application or the upcoming cohort's instructors, sometimes it's a question about the projects in the Metis curriculum, and sometimes it's just an exploratory call to feel out Metis and learn more about the program. Some people also want to see the campus, so I give them a 1:1 tour to offer them a feel for what it's like to be at Metis and see the buzz of student life. Whatever it is, I try to make myself available and help people make a challenging and exciting move.

4. Access To A Detailed Curriculum: What You See Is What You Get

You need to view a detailed curriculum so you can decide if the tools and skills you'll be learning align with your career goals. Unfortunately, some bootcamps are vague about what will be covered. They may offer only a high-level overview with a one-liner describing what will be covered each week. It's best if you can access the full curriculum to learn as much as possible about which skills you'll learn, how much time you'll spend learning them, and in what order, etc. Once you have this information, you'll feel much more confident making your decision.

5. Reviews Matter: Alumni Know Best

Sites like SwitchUp and are solid platforms for you to learn more about student experience, quality of instructors, and general pros and cons through the eyes of students who recently finished bootcamps. These reviews are great because you can read from someone who was just like you a few months ago and is looking to help you make your decision. You can also use reviews to get a general health check on things you may not have thought about, but that impact the program, such as changes in curriculum, a recent round of staff layoffs or canceled/delayed cohorts, acquisitions/mergers, etc. As part of the puzzle, these reviews will shed light on students' experiences and things worth considering to make an informed decision.

I hope that equipped with this information, you have a better understanding of the value offered by the new educational paradigm that is the bootcamp model, as well as a deeper sense of the critical importance of admissions processes at these programs.

If you would like to learn more about Metis Data Science, read what alumni have said on SwitchUp.