Completion of several prerequisites for a Master’s in Data Science program is required before data science majors can begin their professional programs. Prerequisites often include a variety of general education as well as program-related courses that prepare students for more advanced areas of study. Although these prerequisites may differ somewhat from one educational facility to the next, five of the most common are discussed briefly in the sections that follow.
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Data and Information Management
One of the most basic prerequisites for a Master’s in Data Science program is the completion of a course known as Data and Information Management. The main focuses of this class are the tools and foundational concepts in data and information management. Common areas of study include data analysis skills, data assessments, data validation, creating data structures and analysis reports, and common technologies used in data and information management.
Foundations of Data
Another important prerequisite for a Master’s Degree in Data Science is the course referred to as Foundations of Data. In our current world where tremendous amounts of data are available at just the touch of a button, it is crucial for data science majors to learn how to handle this large amount of information. This course focuses on understanding Big Data and other important topics such as data verification, data analysis techniques, open source tools for data science and analysis, and privacy and ethics in data science and analysis as set by the Data Science Association.
Risk Assessment and Optimization in Data Science
Risk Assessment and Optimization in Data Science is yet another common prerequisite for Master’s in Data Science degree programs. When employed in occupations that handle large amounts of data, it is highly important to use that data to the best of its advantage. This course teaches students how to assess the levels of relevancy of data and its impact on various business operations. Other areas of study included in this course are such topics as identifying micro and macro-level risks, evaluating risk management programs, and risk assessment policies and strategies.
Foundations in Statistics
Foundations in Statistics is a mathematics course that is a basic prerequisite for a broad range of college and university programs including Master’s in Data Science programs. During this class, students will examine the role of statistics in quantitative research and learn how to calculate and solve basic statistical problems. Through various case studies, students will also learn how statistics is used in research situations and when analyzing real-world data.
Decision Methods and Modeling
Decision Methods and Modeling is another prerequisite that is typically included in Master’s in Data Science Programs. The main focus of this course is to teach students how to interpret the results of data collection and research. During this course, students will learn how to do such things as evaluate data collected, interpret data collected, and recognize trends in data. Other areas of study include risk assessment and optimization, predictive modeling, data warehousing, data mining, and decision support system development.
Data science majors will need to complete various prerequisite courses before they can begin their master’s degree programs. And while there are several such courses required for these programs, five of the most common prerequisites for a Master’s in Data Science program are discussed in the previous sections.