The Value of Data Science Microcredentials Within Higher Education
Highlighting Marketable Skills in Data Science
Data science is a rapidly growing field with a high demand for skilled workers. Higher education institutions are increasingly offering microcredentials in data science to meet this demand.
Microcredentials are short, focused programs that can be completed in a relatively short period of time. They are designed to provide students with the skills they need to be successful in the data science workforce.
Benefits of microcredentials
- Data science microcredentials can be used to identify marketable skills in data science. By completing a microcredential, students can demonstrate their proficiency in a specific area of data science. This can make them more attractive to employers looking for workers with particular skills.
- Data science microcredentials can be used to upskill or reskill workers. In today's rapidly changing job market, workers need to be able to keep their skills up-to-date. Microcredentials can allow workers to learn new skills or deepen their knowledge of existing skills.
- Besides the benefits for students and workers, microcredentials can also benefit higher education institutions. By offering microcredentials, institutions can attract new students and generate additional revenue. Additionally, microcredentials can help institutions stay ahead of the curve in terms of the skills needed in the data science workforce.
4 Ways that microcredentials can be used to identify marketable skills in data science
- Microcredentials can be used as a pre-requisite for admission to a data science program to ensure that students have the necessary skills before they begin their studies.
- Microcredentials can be offered as part of a data science program, allowing students to gain the skills they need in a specific area of data science while still in school.
- Microcredentials can be used to provide continuing education for data science professionals. This allows professionals to keep their skills up-to-date and learn new skills needed in the data science workforce.
- Data science microcredentials can be embedded into courses across disciplines to allow all students, regardless of major, to gain data science experience. This also contributes to a large data-savvy workforce.
Do employers value data science microcredentials?
A recent survey by the Society for Human Resource Management found that 72% of employers are interested in hiring candidates with microcredentials. And, of those employers, 62% said they would be willing to pay more for a candidate with a microcredential than for a candidate without one. As the need for need for data-savvy employees is growing rapidly, employers may increasingly value employees with data science microcredentials for the following reasons.
- In a competitive job market, finding candidates with data science training can be difficult. Data science microcredentials can help employers identify candidates with the skills they need.
- Employers who are willing to cover the cost of training employees may also find microcredentials more valuable than traditional data science degrees since the latter can be expensive and time-consuming. Microcredentials, on the other hand, are much more affordable and can be completed in a fraction of the time and cost.
Overall, employers are increasingly recognizing the value of microcredentials in data science. However, some employers are still hesitant to accept microcredentials due to concerns about the quality of microcredentials programs and the lack of standardization in microcredentials. Despite these concerns, the perception of data science microcredentials issued by accredited institutions is slowly changing among employers. As more and more employers see the value of microcredentials, the demand for microcredentials in data science will likely continue to grow.
Microcredentials are a valuable tool for identifying marketable skills in data science. By offering microcredentials, higher education institutions can help students, workers, and employers stay ahead of the curve in the rapidly changing field of data science. Additionally, microcredentials can also help to improve the quality of data science education by offering students a more flexible and personalized learning experience.