R Coding for Your Career

 In this blog, I will write my thoughts on how learning a programming language, such as R can prepare high school students for their professional goals in the data science field. 

• Data Science offers one of the most promising long-term and rapidly growing career fields of the last decade. within the data science field, we learn to mine, analyze, and transform data to predict a business’s future. we use data to derive and extract meaningful insights which are becoming valuable for a variety of fields from finance to healthcare to academic research.  
•  There is a growing need for up-and-coming generations of students to learn how to effectively transform raw data into knowledge. As students learn biology, chemistry, and physics, I think high school students should start to build a strong foundation in data science early in their educational training to support progressive proficiency in data science later.
• Data analytic skills are an essential part of many career paths, and teaching data science using R in high school will help set students up for success in the future. Most employers in industry and business expect their employees to have a basic understanding of data science and analytics insight. In fact, interpreting, analyzing, and solving predictive problems are core values for business progress. 
• Data science relies on statistical knowledge, which is mainly taught in the mathematics of data management MDM4U Course. To complete this knowledge, students must learn hands-on experience using R programming language.  
• I have been taught MDM4U for a couple of times, I used Microsoft Excel to apply some functions, such as mean, standard deviation, probability, and basic data visualizations. R can do some spectacular graphics, even a simple histogram, which also has the advantage that R is much EASIER than Excel for such basic graphics.  R language provides a comprehensive list of functions to test and learn any descriptive and inferential statistical data analysis. R provides rich tools and packages for data visualization and predictive modeling. 

• In conclusion, it’s crucial that high school students are given coding opportunities in statistics and data science. These skills will prepare them for the workforce that soon lies ahead of them.

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·        Ref: 

https://www.mastersindatascience.org/resources/resources-teach-learn-data-science-high-school/

https://www.bloomberg.com/company/stories/bootstraps-data-science-course-for-middle-and-high-school-students/