Thoughts on Bootcamps, Master’s Programs, Self-Education. How to Prepare for Data Analytics?


4/16/20220 min read

Data science bootcamps can be very beneficial for some individuals. I have seen some people go through these bootcamps and start great careers. Some even land positions at renown companies within months of graduation. Others start at smaller fims and grow with time.

Sadly, there are also bootcamp graduates who don’t land jobs, and eventually go back to their previous careers, if they had one. Choosing between going to a bootcamp, going into a masters program, or learning on your own will depend on a few factors:

  1. Brackground and experience

  2. Learning style

  3. Timeline

  4. Financial Situation

Your Background and Experience

Your educational and professional backgrounds are very important when deciding among bootcamps, masters programs or studying on your own. A bootcamp is fast and while it will try to give you as much information in a short period of time, you’re unlikely to get experience. On the other hand, a masters program will help you get an internship, which will give you some experience before looking for full time positions. In other words, it is crucial to be able to show some professional experience before looking for a full time position.

Professional experience in a related field like IT, engineering or biology will be helpful for someone transitioning into data science and analytics. This person is a good candidate for taking the self-education route.

In my three years in the field, I have seen three kinds of folks break into the field more successfully than other groups: STEM Phd’s, Data Science Masters graduates, and seasoned IT/Engineering/Science professionals who have learned the necessary technical skills.

I personally attended a bootcamp, and I did notice some patterns in the folks who landed a job vs those who didn’t. Below I summarize them.

Characterisitcs of bootcamp students who succesfully landed jobs after end of program:

  • Went into bootcamp with industry experience and at least a Bachelors or advanced degree in STEM field.

  • Had solid professional network in the geographical area where they job hunted.

  • Started job hunting and networking before end of bootcamp.

  • Open to interviewing for jobs with smaller companies.

  • Getting their foot in the door was their priority. They knew the positions are larger companies would follow.

  • Open to business intelligence and data analyst positions.

  • Tool agnostic.

Characterisitcs of bootcamp students who did not land jobs after end of program

  • Little to no industry experience.

  • Poor networking skills.

  • Focused more on learning concepts and tools than on job hunting.

  • Unrealistic salary expectations for first job.

  • Unwilling to take jobs with small companies, temporary work, or positions without title data scientist.

A piece of advice for anyone braking into the field. The first position you take in the field is not necesarily where you will stay for years. The tech job market is very fluid and it’s common for individuals to switch jobs within 2-3 years. The field is hot. More opportunities will come as you gain experience.

Your learning style

Ask yourself the following questions:

  • Am I dilgent enough to stick with courses if I don’t have to physically go to class?

  • Am I independent enough to succeed without classmates to meet and study

If you are, then go for the online courses and create an online community that you can bounce ideas with. You can answer questions when they have them and they can give you a hand when you need it. There are more than enough resources floating around tha you can learn from. These resources are available in the form of tutorials, blogs, podcasts, github code posts, YouTube videos. Many of them are completely free, others are available at very affordable prices.

If instead, you need to go to class, then an in-person course is more appropriate for your learning style. Your options then become:

  • A 12-week bootcamp

  • A 9-month certificate course

  • A 1-year accelerated masters program

  • A 2-year traditional masters program

If you must have a degree, then a master’s program is best for you. Just keep in mind that these programs can run you around $50K and take longer to complete. Will you be able to keep your current job while you complete this program? Give it some thought.

Your Timeline

It’s important to determine how long you have to master the tools and basics, to make a portfolio, and to start the job hunting process. Determine a timeline that fits your current living situation and your desire to get into the field.

How long do you have to make the transition to your first job? Your educational background, professional experience, and time availability will determine this. People with STEM degrees typically have a leg up in the educational side. That also goes for those with experience in jobs that require heavy quantitative chops.

If you’re currently enrolled in school, then you’re in a good position. You can find resources at your current institution and start your learning journey. Moreover, universities and colleges are great places to network and find mentors. Attend talks hosted by the departments of Statistics, Biostatistics, and Computer Science. Ask questions, find out about events, or campus groups that might be able to help you with direction.

Additionally, if you’re currently employed in a different field, you’re in a good situation. You can start attending meetups after work and learn more about the analytics industry in your area. Network and find mentors who can give you the direction you need.

Your Financial Situation

Let’s talk about the elephant in the room. How much money are you willing to spend to become job ready?

If your answer is very little, say less than $100, then you’d better find the free resources in the web and start studying. It’s doable. It’s harder. Make sure that if you’re in this group, you have enought time to go to meetups and network in your area.

If money is not a problem, but time is the issue, find part time certificate or master’s programs which allow you to keep your current job. For example, the University of Washington offers a MS in Information Systems and Seattle University offers a MS in Business Analytics, both part-time. I know about these programs because they’re both in my area.

A bootcamp can be tough for many folks because it requires you to attend it full-time. If you’re currently working, it would mean to get 12 weeks of vacation or quitting your job. Most adults are unable to live without income for that long.

Closing Thoughts

You must remember that no person or institution can garantee that you will get a job when you finish their course or program.

There is an abundance of learning materials available online in the form of blogs, forums and MOOCs (massive open online courses). And you don’t have to read or complete all of them to get a data scientist job.

It is no secret that having an advanced STEM degree is a big plus in trying to land your first data sicentist position, but it is not the only path.

Network in your area and find mentors who can provide more personalized advice to fit your case and goals.

Stay focused and curious!