3 things every student should learn in a data science program

Studies show that 95% of employers say data science skills are hard to find among candidates, and that by 2021, students with data science and analytics skills will be twice as likely to get a job.

So it's no surprise that many higher education institutions are launching or expanding academic programs related to data science. In a recent article for EdTech magazine, Meghan Bogardus Cortez discusses three lessons every student should learn in a data science program, based on a report from the National Academies of Sciences, Engineering and Medicine (NASEM).

Lesson 1: How real data scientists work. Real-world data problems will be more complex than the problems students work on in class. To prepare students to correctly approach a wider range of problems, NASEM recommends showing students how real data scientists work through problems and teach them a six-step data science work cycle, similar to the scientific method used in other fields.

Automation is coming. Is your analytics program ready?

Lesson 2: What real-world applications look like. As other experts have argued, introducing real-world applications as early as possible can make content more engaging and accessible, the NASEM report notes. For example, Southern Connecticut State University students use IBM Watson to analyze data from local businesses to help them operate more efficiently.

Lesson 3: With great power comes great responsibility. Employers expect data scientists to do more than solve problems; they also expect them to protect the organization's data and use it ethically. NASEM advises all data science programs to teach students about the ethical concerns related to data, such as respecting privacy, collecting data honestly, and keeping data secure (Bogardus Cortez, EdTech, 12/5).

There were 400,000+ job postings for this skill in 2016. Are you teaching it?


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