Students pursuing a master's degree in economics and data science explore applications of data science in the field of economics, in addition to advanced economics concepts. This master's program discusses technical and statistical concepts useful for economic analysis and drawing insights for better decision making. Information about a few core courses and general admission requirements for this master's degree are described below.
Master's in Economics and Data Science: Common Courses
A master's degree in economics and data science can be completed within 20-24 months. This program requires 30-36 credits, which typically include a hands-on project and some of the core courses presented below.
Principles of Microeconomics and Analysis
This type of course typically explores the fundamentals of microeconomics, such as understanding consumer behavior, different types of market structures, and functioning households and firms. This course could also cover key analysis concepts of microeconomics such as demand measurements and game theory. Topics related to economic capitals, analysis of investments, market behavior and uncertainties might be a crucial part of the curriculum. Understanding perfect and imperfect competitions, analyzing firm behavior in market failures associated with demand and supply could be part of this subject.
Courses related to econometrics typically present applying statistical analysis methods to economic data. It might also discuss various regression techniques to understand and analyze economics with a policy focus. The introduction of several software tools and programs used for statistical concepts might be a part of this course. Topics related to designing empirical models for economic problems, sample collections, time series concepts, result analysis could be a part of this course.
Concepts of Database
This course might introduce different types of databases such as relational, No SQL, object-oriented databases. Database methodologies and techniques for handling data, designing database models, and concepts related to data maintenance could be part of this course. Also, data distribution concepts, data administration techniques, SQL programming, and other database programming concepts could be part of this course. Additionally, hands-on tasks might be included to provide technical work experience to the students.
Bigdata and Management
Students explore the fundamentals of big data, data management techniques, methodologies, and phases in handling big data. It might also include topics such as data warehouses, cloud database services. Big data management concepts like data collection, data mining, data cleansing, processing, and analyzing could be a part of this course. This course might introduce data processing software packages and statistical analysis tools.
Concepts of Business Intelligence and Analytics
Typically, this kind of course introduces processes and technologies required to convert raw data into meaningful insights. Students can learn to design and implement business intelligence models for the strategical analysis of economics data. Technical concepts and software tools required to build business intelligence applications and could be a part of this course.
Candidates with an undergraduate degree are eligible to pursue a master's degree in economics & data science, and schools generally require students to have a minimum cumulative GPA of 2.75 to 3.0. Although typically, no particular background is compulsory for admissions, some programs might suggest an economics background, while some others may demand students to complete foundational courses in economics and analytical statistics. GRE/GMAT with strong quantitative scores might be required. Students might have to submit official transcripts of previous education. Additionally, some schools prefer a resume, statement of purpose, and two to three letters of recommendation.
Applicants with an undergraduate qualification are eligible for the master's degree in economics and data science. In addition to economic concepts, students can explore the analytical skills required for better economic analysis and decision making.