After writing for years about the benefits of certificates and short-term credential programs, especially for working learners, I had begun to feel inauthentic, like a self-help guru who doesn’t take her own advice. So I finally enrolled in one this spring: Google’s “career certificate” program in data analytics, available online through Coursera for $39 a month.
With more than 6.5 million learners enrolled worldwide, Google is one of Coursera’s “top instructors,” offering a multitude of certificates in a panoply of languages from Arabic to Spanish. I thought I was gunning for a certificate. What I actually got was a lesson in humility.
Google’s data analytics program is its most popular offering. The program consists of eight separate courses with titles like “Prepare Data for Exploration” and “Process Data from Dirty to Clean.” Course materials consist of short videos, quizzes, readings, and optional practice activities. Students can also post on message boards to engage with other enrollees.
Production values are slick, with soft lighting and catchy music, and the content is high quality—this is Google, after all. Modules are succinct and logical; the instructors, all of whom are Google employees, are lucid and charismatic. The course does an exceptionally strong job of explaining what data analysts do, with mini monologues by upbeat Google workers describing their backgrounds and jobs. Also laudable is the focus on soft skills, like collaboration and teamwork. One module, for example, talks about the importance of finding mentors and building networks, while another segment tackles how to handle conflicts with colleagues. Instructors are also refreshingly diverse. In an industry infamously dominated by white men, only one instructor appeared to meet that description.
But the program’s central conceit—to “equip participants with the essential skills they need to get a job” with no degree or prior experience required—is also its central weakness. Google’s aim to make the program accessible to all learners means the material is basic, and the pacing frustratingly slow. It’s not until the final module of Course 4, more than 100 hours into the program, according to the syllabus, that students begin to work with formulas for data analysis, like calculating averages. It’s not until the very end, Course 7, that students finally get to work with the programming language R, and even then, we were only introduced to a handful of commands.
Though I started out diligently enough, watching every video, clicking every link, and trying to channel the enthusiasm of my Google teachers, the format quickly turned monotonous. What should have been a progression toward mastery became an exercise in sheer endurance—which is about when I started to cheat.
I began watching videos at double speed, skipping optional exercises, skimming through readings, and passing quizzes through trial and error. You only need 80 percent to pass a quiz, and you can take them as many times as you’d like. I also discovered that the written responses required in some quizzes didn’t have to make much sense. I once typed in, “The quick brown fox jumped over the lazy dogs performing data analysis,” and earned 100 percent.
According to the American Council on Education, which evaluates academic programs, my Google data analytics certificate program should have taken 175 hours and more than six months to complete. My shortcuts got me mine in about two and a half weeks. My certificate—a digital document that I can share with employers—declares my competence in “tools and platforms including spreadsheets, SQL, Tableau and R.” In truth, my knowledge of the programming languages SQL and R goes about as far as knowing they’re not just letters of the alphabet.
One thing I did learn is the difficulty of completing a self-directed program with static content. Humiliatingly, I learned that I personally lack the discipline and dedication to upskill myself. As I clicked through video after video, I could feel the press of chores and other assignments, while my aspirations for learning withered. My dog suddenly needed a walk; I remembered emails I had to return and errands I needed to run.
I can only imagine how much more challenging this must be for students in different circumstances than my own—workers with physically demanding jobs, small children at home (my kids are big), or stark financial pressures, or those who are perhaps counting on this course as a gateway to a better life. Coursera and Google do not disclose completion rates, and there are many reasons students don’t finish, but I noticed that while Course 1 in my data analytics program listed 1.9 million enrollees in July, just 328,000 had enrolled in Course 8. That suggests an 83 percent attrition rate.
Policy makers and pundits often talk blithely about re-skilling and upskilling American workers, as if access to a training program is all it takes to transform 20th-century-trained workers into a 21st-century labor force. But my experience underscored that people also need a support network—access to other humans, who can provide mentorship, guidance, motivation, and community. Almost anybody, including those who have been out of school for a long time, is theoretically capable of learning a complex set of new skills. But they can’t be expected to do it on their own.
A second lesson I learned is that there’s no free lunch when it comes to education and training. Data analyst jobs pay as much as they do because it’s impossible to learn everything you need from a single online course. Google acknowledges as much in the final modules of its program, where it encourages students to build a portfolio and provides extensive links to additional tutorials in coding, data visualization, and other skills. Providers need to make clear that a certificate is only the first step toward a career, not a substitute for the deep knowledge, professional networks, and work experience someone needs to truly succeed in a field. (See main article.)
I still believe that quality certificate programs can help jump-start, restart, or advance careers. But they’re neither a stand-alone solution nor a silver bullet. My experience in the educational trenches provided another useful reminder: that the champions of policy prescriptions sometimes need to take their own medicine.
