What does it take to succeed in a Data Science Program?

Meet Anne! She’s the Senior Instructor and Associate Chair at the University of Colorado, Department of Applied Mathematics, and has been an educator since 1984. This semester, she’s teaching a Foundation for Data Science course on Coursera and was kind enough to offer four tips to learners interested in the field of Data Science.  

Self-motivation

Anytime you’re learning online, you need to be self-motivated. You have to really want to spend the time on the material. It helps if you have an end goal in mind – a specific type of job – or you want to move into a new field. 

Knowledge of Mathematics 

This material can be challenging, but we’ll work with you and we try to help you get to that Aha! moment where you start to see how the various topics that we’re covering are connected. At the most fundamental level, the language is mathematics. If you understand that language, then you’re able to create all sorts of stories in whatever field you’re interested in. That applies to every technical discipline. Data science is not an impossible field, but it does require a good understanding of mathematics and a willingness to learn new material. So you really need to be successful from a mathematical standpoint. You need to have a good understanding of calculus One and Two and some linear algebra, even in the introductory courses in the statistics and data science track. 

Determination

As a student in a program like this, you have to find a way to balance life, work, and school. Learners have had family issues come up, and we’ve made accommodations for them. With Coursera, we’re able to offer you flexibility that you won’t find at a traditional institution. That’s what allows you to receive an education while managing work and family. In the long run, your success will result in an increase in self-confidence and self-worth, and you’ll gain new skills that you can apply in your current job, or to move to a different job. 

Self-awareness

I always tell students that you need to follow your interests. Be interested in the area. You shouldn’t do it because you think it’ll get you a better job. That’s an excellent byproduct, but if you’re not truly interested in the material, I think it’s really hard to make that long term commitment to go through this program. If you really like the material and you’re curious about it however, I think it’s a great program at an absolutely top notch university, and can really help set you up for success down the road. 

Thanks so much, Anne!

We hope you enjoyed hearing from Anne as much as we did. If you’re interested in learning data skills and possibly earning a credential, check out the Probability Theory: Foundation for Data Science course – part of the Data Science Foundations specialization available on Coursera. You’ll learn the foundations of probability and its relationship to statistics and data science from leading industry professionals like Anne. 

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