Subscribe to DSC Newsletter


I'm considering a career change into data science, and wondering what you think would be the best way to break in.

My main question for you is, what are your recommendations for getting started, and are there any particular educational programs you feel are best?

I have been researching online learning programs and plan to start some basic programming modules to test my aptitude for it. I learned a tiny bit of SQL last year while working as a genetic curator with an incredible development team to build a world-class genomic database, which helped open my eyes to the growing and fascinating world of data science.

I've looked at Udemy, Udacity, Khan Academy, Coursera, and EdX for fundamental courses - do you have any preferences? I'm also considering the Master of Information in Data Science Degree from Berkeley, but want and need some entry-level programming experience before I commit to that expense.

Ideally, I would like to find work in the field while I study, but other than an aptitude for learning, have little relevant experience. I have a B.S. in Biology, spent 10 years in zoology, field biology, & conservation research, then transitioned into the lab in pharma bench research, and then into operations. I now have 10+ years small business management experience, including sales & marketing, and managing various CRM databases. I am currently working as a marketing consultant to pay the bills, but I miss science and am passionate about mission-driven work that makes a positive impact in the world. I am currently most interested in how a data science career can be applied to the burgeoning field of translational medicine, as well as applications supporting environmental conservation and sustainability.

Any recommendations to help me get started the best way possible are greatly appreciated. Thank you!!!

Views: 1036

Reply to This

Replies to This Discussion

I would pick Coursera if you have time and patience for a perfect start , or Udemy for a quick start but on a high level self-learning pace PLUS do research on your  own and less expensive !

Great question! I think there are many ways to go. Here is a link to a "NanoDegree" program that we have partnered with Udacity to create:

Introducing the Udacity Predictive Analytics for Business NanoDegree

From that page you can also navigate around our community (no obligation, of course), to get a feeling for the different roles in analytics.

Only here to help! Good luck with your endeavors!

Wonderful, thank you so much!

No problem, Wendy! I thought of you later today when I posted this: Product Training to answer another question on LinkedIn. Hope all of this is helpful.

Hello Wendy.  We have very similar backgrounds and interests.  I also have a B.S. in biology and have spent over 10 years working in chemistry research and production, but I do not have any business experience.  I also became interested in data science and have found all of the providers that you listed to be very helpful - especially Coursera and EdX.  I too have little relevant experience in data science, but I have been, and continue to be willing to learn.

Great, thanks for the feedback James! Good luck in your continuing education and career goals!

Thank you for the feedback Narender!

Narender Reddy Kanuganti said:

I would pick Coursera if you have time and patience for a perfect start , or Udemy for a quick start but on a high level self-learning pace PLUS do research on your  own and less expensive !

I think, familiarizing yourself with Python is probably a good way to start. Python definitely offers the most Data Science libraries these days.

When you are comfortable with Python, you should take a look at a couple of the most commonly used libraries like: NumPy, Pandas, Scikit-learn. You will find very active communities for all of the popular Python Data Science libraries as well as many forums and tutorials.

Sounds like good advice, thank you Joe!



  • Add Videos
  • View All

© 2020   Data Science Central ®   Powered by

Badges  |  Report an Issue  |  Privacy Policy  |  Terms of Service