Get As Many Data Science Skills As You Can In College

By michael mannen on April 15, 2019

When most graduates when they enter the job market, they are shocked by the reality they face.

The stark difference between being a full-time employee and full-time student are as different as night and day.

Data Science skills or employees are becoming as necessary as sending an email or reading or writing. Decisions are being made based on data and data is being collected on everything. If you do not want to become a full-time data scientist, possessing the skills of a data scientist can be useful to any career. Most colleges do not have undergraduate programs in data science. And a variety of majors will prepare you to become a data scientist.

You do not necessarily have to major in Mathematics or Statistics to get data science skills to help you get employment. You do not even necessarily have to get a minor in a relevant field. Taking a few programming and math courses can suffice. You can also study online at EDX, Udacity, or Coursera to get the necessary skills to supplement your undergraduate education. These websites offer courses and certificates that help you gain skills related to data science.

via Pexels

So what data science skills do you need to succeed? Or at least survive?

First, you have to know how to program. This means you should learn statistical languages such as R, Python, and database language such as SQL. Also, for the social sciences and public health, it is helpful to learn STATA and SAS. Vital to getting better as a programmer is a significant amount of practice. There are a variety of publicly available datasets that you can practice on to get better. And the more you practice, the more work samples you will have to show employers. Sites like Github allows you to showcase your work samples and freelance work to potential employers.

As a data scientist, it is critical to have a fundamental understanding of Statistics and how to do statistical tests. Also, when datasets are made, they are rarely perfect and learning how to alternate datasets for structural analysis is essential. And, fundamentally, learning how to visualize and communicate results from analyzing data may be the most critical step for any data scientist.

There are still some fundamental math courses that would help to learn and master while even in undergraduate. These include Linear Algebra, Calculus, and one-course statistics. However, from these fundamental skills, you can do anything in data science.

As you progress, you can learn more advanced topics such as Machine Learning and software engineering.

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