New SAS Program for Students Charts Path From Analytics Skills to Dream Job

  • Sas Skill Builder for Students Connects Sas Learning Pathways, Certifications and Career Resources

With continued high demand for data science talent, analytics leader SAS has launched a new program for higher education students to learn analytics skills and earn valuable certifications sought by employers. SAS Skill Builder for Students is a free, global, 24/7 virtual learning portal that offers access to SAS software, e-learning and certifications, as well as career advice and ways to connect with employers.

SAS Skill Builder for Students helps higher education students learn analytics and data science skills and earn valuable certifications sought by employers

“It’s never been easier for students to learn SAS and apply those skills in a career they love,” said Lynn Letukas, Senior Director of Global Academic Programs and Certifications at SAS. “SAS Skill Builder for Students highlights our continued commitment to growing the next generation of analytics experts and connecting employers with the talent they need.”

Natalie Ziemba is a member of that next generation. She is intrigued by the power of data in research and used her SAS expertise to land a job as a programmer and analyst at Duke Clinical Research Institute where she uses SAS to analyze FDA clinical trial outcomes.

“I was hunting for jobs that let me pursue the data side of research. The SAS@ knowledge I gained in school and through certifications was exactly what I needed,” said Ziemba. “I get to spend all day using SAS and solving puzzles that can improve public health.”

Ziemba learned SAS while earning her online Graduate Certificate in Applied Statistics and Data Management at North Carolina State University and is a SAS Certified Specialist in Base Programming Using SAS 9.4.

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The path to a great analytics career

Last year, more than 143,000 job postings listed SAS@ as a desired skill, according to Emsi Burning Glass, an aggregator of labor market data. SAS Skill Builder for Students can help more students seize those jobs by providing access to:

  • Free cloud-based software: SAS@ OnDemand for Academics and SAS® Viya® for Learners.
  • Free e-learning: Courses in foundational skills like data literacy and point-and-click data analytics, programming, visual analytics and visual statistics, statistical analysis, predictive modeling and machine learning.
  • Certification pathways to simplify the journey to data science certification and other valuable SAS certifications.
  • Exclusive certification exam discounts for those who register.
  • Badges that signal valuable skills to employers in areas such as data visualization and machine learning.
  • Career resources to inspire students and help them succeed. Students can explore what it means to be a data scientist and data analytics professional, how to set themselves apart and connect with employers offering work that taps into their passions.

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An academic email domain is required to access SAS Skill Builder for Students.

Thriving in a data-driven world

SAS Skill Builder for Students incorporates data from a variety of industries to gain valuable and relevant experience. Students can also learn one of the most valuable skills for success in today’s society and workplaces: Data literacy. In a world awash in dis- and misinformation, it is critical to be able to consume, interpret and understand data. SAS Skill Builder for Students includes access to Data Literacy Essentials, a SAS@ course that introduces data basics and strategies for using and interrogating data, discovering meaning, making decisions and communicating data. The course follows the journeys of a concerned parent, a small business owner and a public health expert, who each use data to navigate and problem-solve through the pandemic.

The course also focuses on the ethical challenges of working with data. Data ethics refers to how we seek out, interpret and present data responsibly, including the moral judgments we make when working with data. The course covers how biases influence the ways we interact with and communicate data and provides guidance on ways we can work with data more responsibly.

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