Data science in the educational curriculum – how and why it should be implemented
Data science has gained significant hype in the past couple of years, but there are still only a few individuals who are aware of its real purpose.
So, what exactly is data science? Data science is an interdisciplinary field that combines science and computing to extract, manage, process and interpret data for the derivation of actionable insights to solve real-world problems.
Furthermore, data science incorporates various disciplines such as data mining, machine learning, predictive analytics, data engineering, data preparation and data visualization, as well as statistics, mathematics and software programming.
Growth in global data
We are living in the age of artificial intelligence and big data, which, simply put, is the era of the fourth industrial revolution. The world drives on data, with dependency on the internet and digital technology becoming increasingly more blatant. In the last couple of years, there has been a massive surge in the availability of data. Every day, 2.5 exabytes of data are created, while the global data is expected to exceed 175 zettabytes by 2025.
This stupendous saturation can be sourced from mainly two recent changes. The first one is the accessibility of data fed by smartphones and the internet. The second one is the substantial advancements in the quality of software tools for data analysis.
This significant data explosion has left many Americans overwhelmed. The main reason for this can be derived from the fact that not many of us are comfortable, skilled, or have the appropriate understanding when it comes to handling data, despite its vital importance in regard to understanding our world and making educated decisions.
Despite the various revolutions in technology, our K-12 curriculum is still stuck in the industrial age. To eradicate this data illiteracy, our education system and institutes must prioritize and enforce data-science education for all students. In this way, we can help them get a better understanding of how to diagnose the large amounts of data being produced every day.
Promoting data science in educational institutes
To establish improvements, we can continue in a number of ways. Firstly, educationists at the state and district levels can update the modules in mathematics, statistics, and other domains to highlight data science and computational fluency. Secondly, colleges need to reform their admissions criteria and accept coursework regarding data science as proof of rigorous mathematics preparation. Lastly, the state and federal policymakers should bring about a significant increase in funding to equip institutes with the necessary means to teach the data science curriculum effectively.
Even now, there are some organizations that understand the importance of the applications of data science. Among these organizations is Worcester Polytechnic Institute (WPI), which is well-known for its experiential learning model and provides real-world knowledge regarding various in-demand technology roles. WPI offers an exceptional Online Master’s in Data Science where you can learn to derive meaningful insights from raw data and enunciate them into innovative solutions.
From artificial intelligence and machine learning to data system administration and cyber security, data science spans various disciplines. Depending on what you wish your focus to be directed on, you can pick from the following alternatives.
Master’s in data science
Earning a degree in data science can provide a comprehensive understanding of the fundamental mathematical and statistical concepts and how they are incorporated into algorithms and machine learning techniques to devise solutions to various data processing and analysis problems. You can gain the ability to write clean and efficient code in industry-recognized languages, which include Python, R, and SQL in particular. Moreover, you can also master the art of data handling, data manipulation, data mining and visualization techniques.
Master of Science in Information Systems
A master of Science in Information Systems (MSIS) is a STEM degree that focuses on training students in the core concepts of computing and business to analyze, design, maintain and manage information systems in industrial, government and non-profit settings.
This degree prepares you for a professional career position in today’s data-dependent and data-intensive economy. It teaches you the core concepts used frequently in data analytics and business intelligence with both conventional statistics and modern machine learning techniques. If you are looking for more of a data science bent, seek out an MSIS program that concentrates on or emphasizes data analytics or business intelligence.
Master’s in business analytics
A master’s in business analytics equips you to make data-driven and evidence-based decisions that drive transformation within businesses. It uses sophisticated analytics techniques, including social network visualization, and state-of-the-art programming languages including R, Python, SQL and NoSQL. This can help you understand and predict consumer, market and world economic trends, and also help you get insight into how data influences company decisions and elevates their overall performance.
Also, this specialization provides a practical foundation in the core concepts of data. Some practical skills in the programming languages mentioned are needed to unlock the true value of data.
Other related degrees
Besides the aforementioned degrees, you can opt for a master’s degree in computer science, computer engineering, or cyber security, which are disciplines linked to data science. Additionally, they can prepare you for a career in data science – which is becoming increasingly valuable by the day.
Earning a master’s degree
Normally, it takes about 12 to 16 months to complete a master’s degree if you are a full-time student, though one-year options are available in some instances. The requirements for admission vary from one program to another. However, getting into a master’s program requires a bachelor’s degree, which may or may not be specific to a certain field.
Prerequisites may include courses such as calculus, intro to computer science, and statistics. Moreover, you might need work experience, a statement of academic purpose, and letters of recommendation to qualify.
Implementation of data science in the educational curriculum has become necessary, especially since the massive outpour of data. Not only will enforcing studies regarding data science at school and college level help prepare students for better careers, but it will also provide them with a better understanding of what is happening worldwide.