Coursera Launches LevelSets to Help Learners Develop Critical Skills Faster

  • Offers broad range of new assessments to determine proficiency in essential skills including data analysis, cloud computing, and machine learning

Coursera, Inc. announced the launch of LevelSets, a new assessment tool designed to help learners determine their current proficiency in key business, technology and data skills.

“LevelSets help motivate learners to enroll in recommended courses and enable them to develop job-relevant skills faster. These assessments determine where training should begin, and create a clear development path for learners featuring high-quality content that aligns to their skill goals.”

Offered as part of the company’s enterprise platform, LevelSets currently includes over 20 different skill assessments created using machine learning programs. The initial assessments will test proficiency in high-demand data and analytics skills including data analysis, cloud computing, machine learning, Python, and SQL, among others.

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“Rapid digital transformation is increasing the urgency to acquire in-demand skills. However, lack of time and frustration over not knowing what courses to take are major barriers for learners,” said Leah Belsky, Chief Enterprise Officer at Coursera. “LevelSets help motivate learners to enroll in recommended courses and enable them to develop job-relevant skills faster. These assessments determine where training should begin, and create a clear development path for learners featuring high-quality content that aligns to their skill goals.”

The LevelSets offering enables learners to:

  • Save time and develop skills faster – Learners can complete assessments in less than 15 minutes to identify existing skills. This allows them to not waste time on content they have already mastered and focus on courses that can increase skill proficiency faster.
  • Experience a unique learning journey with targeted recommendations – Once assessments are completed, learners receive targeted content recommendations that match their proficiency level to ensure the right starting point in their skill development journey. This allows learners to avoid taking courses that are too rudimentary or too advanced.
  • Develop stronger motivation to learn new skills – By providing a deeper understanding of current skill levels and recommending specific content to improve proficiency, LevelSets can increase learners’ desire to enroll in and complete relevant courses.
  • Showcase existing skills knowledge – The assessments enable learners to demonstrate their proficiency in high-demand skills needed to unlock new career opportunities.

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Customers such as Fidelity, Ingka IKEA, Pfizer, and Thermo Fisher Scientific are early adopters of LevelSets. Initial data suggest that learners within these companies are 3x more likely to enroll in a recommended course within 1 day after taking a LevelSet assessment. In addition, course completion rates have increased 66% among those that have completed assessments.

By completing a LevelSet assessment, learners will gain access to world-class content recommendations from leading university and industry partners. This content is delivered through SkillSets, job-based learning programs that help learners develop specific skills for specific roles. Content recommendations include:

  • Machine Learning for All by Dr. Marco Gillies from University of London
  • AWS Fundamentals: Migrating to the Cloud by Seph Robinson and Sean Rinn from Amazon Web Services
  • Understanding and Visualizing Data with Python by Professor Kerby Shedden, Brenda Gunderson, and Brady West from University of Michigan
  • SQL for Data Science by Sadie St. Lawrence from University of California, Davis

LevelSets is currently available to companies, universities and governments that have implemented Data and Analytics SkillSets. Coursera plans to make LevelSets available across its portfolio of over 300 SkillSets early next year.

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Courseradata and analytics skillsdigital transformationin-demand skillsjob-relevant skillsmachine learning
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