Data scientists draw inferences from large populations based on samples. Measuring every individual or unit is an impossibility, therefore, data scientists consider the potential variability among samples before making conclusions about the entire population.
In the Data Science Essentials certificate program, you will use a simulation-based framework to understand uncertainty in your data. You will use R, a statistical programming language, to gain hands-on experience in performing simulations. Additionally, you will use resampling techniques to understand numerical variables. You will establish a prediction rule where one numerical variable is used to predict another. You can then utilize the errors from linear regression to compare prediction rules and determine which ones best fit your data.
This course places a strong emphasis on practical learning to help you enhance your programming skills and develop an understanding of how to effectively handle uncertainty in data science.
Enhance your data science toolkit, gain proficiency in understanding and quantifying uncertainty, and empower yourself to make informed decisions in the face of variability by enrolling in the Data Science Essentials certificate program offered by Genashtim, in collaboration with eCornell.
eCornell courses are approved by SkillsFuture Singapore for SkillsFuture Credit as well as by HRD Corp Malaysia under its HRD Corp Claimable Course Scheme.