Br8k into data
Avoid the mediocre middle
How to choose online courses for a career in data:
Dear Br8ke into data,
Are there truly useful educational resources?
-Ops looking for change
Dear Br8ke into data,
What do you think about the data analytics program offered by DataCamp and Code Academy?
-Student in Seattle
TLDR
I got a lot of mileage out of Udemy courses, local community colleges, and my local library
Why we study
I am going to answer these questions at the same time because they are really the same question.
Online technical courses try to sell us on a number of different benefits, mostly centered around getting a job as a data scientist, data analyst, or data engineer.
Our goal for course work is to:
- Get a job
- Acquire the skills needed for that job
- Meet students and teachers who can form the nucleus of a professional network to help advance our careers
The problem is that it isn’t a straight line between taking the course and getting a job.
A school helps students get jobs in three ways:
- Its reputation is so good that employers recognize that recent graduates are high-quality applicants.
- It has a career placement service that actively tries to get recent graduates and alumni jobs.
- It has a well-organized alumni network that connects recent graduates to older alumni that facilitates networking.
Online technical training doesn’t serve any of those functions. Using the example of DataCamp and Code Academy, their only admissions criteria are whether or not someone can pay, so regardless of how good their education is, they will never have a reputation that gets their graduates interviews.
Likewise, for what they charge, maintaining a costly career placement service is probably not feasible and wouldn’t scale well. A service like this might have a job board, but it isn’t really that different from more public facing job boards.
While they might have many alumni, the nature of online education limits community-building opportunities, and in my experience doesn’t lead to the same camaraderie. Because these services are so young, the bulk of their graduates are in their early careers, and unfortunately, an alumni network consisting solely of recent-graduates/early-career professionals isn’t very valuable.
Online technical training is just that, it builds a technical foundation for your career
You can absolutely learn all the skills you need online. Introductory curricula are incredibly similar.
I have three introductory Python courses in my Udemy account and they overlap about 90% in the subjects they cover. The introduction to Python courses on LinkedIn Learning and Skillshare also cover the same materials.
Whatever platform you take your introductory course on will cover the same material as any other platform.
Knowing that we now have to decide what we are buying, and what we want to pay.
What you’re paying for
I started my career in data by attending a local community college. My first data course cost about $1,200, and was part of a larger certificate program in User Experience Design. Compared to a platform like Udemy, or LinkedIn Learning, I was paying an enormous sum of money. The knowledge I learned in that course could have been had for $10-$20 on Udemy at the time.
The instructor of that course, Anil Batra, is still my mentor. He has served as a letter of reference for three different jobs and gave me the most valuable career advice I have ever received. I can draw a fairly straight line between taking that course and getting my first job in data. It’s the best educational return on investment I’ve ever had.
On the other hand, I learned Python from a $10 Udemy course (or more accurately, 3 different $10 Udemy courses). Being able to write Python dramatically improved my career prospects and I was able to turn that knowledge into a significant pay bump within about six months.
The point I’m trying to make is, be very deliberate about what you’re paying for.
The mediocre middle
If you’re taking someone out to dinner and you want to impress them, you have a few options.
- You could take them out for fine dining which can impress them with a luxurious dining experience
- You could take them to a really good food truck, showing off your knowledge of the local food scene
- You could take them to an Applebees or similar chain restaurant at the local mall
Two of those options are unique culinary experiences at opposite points of the price spectrum. Going to Applebees is the mediocre middle, your meal will be a lot less interesting and you’ll pay twice as much as you would at the food truck.
Learning data science is not that different from eating out; there are expensive ways to learn that come with a high degree of personalization and a chance to make meaningful connections, and there are also incredibly inexpensive ways that cover the technical knowledge but don’t provide much career support.
My problem with DataCamp, and Code Academy is that they’re too expensive.
At the time of writing, Data camp costs $300 a year, and Code Academy charges $240 a year.
There are a lot of ways to learn these skills for less than that. I’m confident that you could learn what you need to on Udemy for under $100, or with aggressive google-fu on YouTube for free.
I’m a big library advocate and I always encourage people to check out the digital resources your local library offers. As I know both of these questions were written by people in Seattle, the Seattle Public Library offers free access to LinkedIn Learning.
Conclusion
Career transitions are “Here too there” problems. The truly useful resources are ones that let you navigate where you are to where you want to be. If you work in operations, advanced spreadsheet skills are a good place to start. Take an analytic mindset and apply it to your work. Solve operations problems using analysis, and then put that on your resume and talk about it.
When you write your resume, be specific about what you can do with various technical skills.
By the way, the advice Anil gave me is, “Start applying for jobs. You can do the work, and if you can do the work, someone will hire you.”
My corollary to that is that you should manage your expectations. Your first job in data will probably not be for a FAANG company, and it will certainly not be glamorous, but once you get in and start solving problems other jobs will follow.
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About
Charles Mendelson was a licensed acupuncturist running his own small clinic and successfully pivoted into a career in data where his job is somewhere between being a data analyst and data engineer.
If you would like to get in touch with him, the best way is LinkedIn.
Originally published at https://charlesmendelson.com on September 27, 2021.
