Applied Economics & Predictive Analytics (M.S.)

The Master of Science in Applied Economics and Predictive Analytics at the University of North Dakota equips students with essential skills in economic theory, data analysis, and predictive modeling. This interdisciplinary program merges economic principles with advanced analytical techniques to prepare students for a dynamic job market. Students engage in rigorous training that encompasses both qualitative and quantitative methodologies, fostering a deep understanding of how to interpret economic data, forecast trends, and guide decision-making.

The course structure combines core courses in applied economics alongside specialized modules focusing on predictive analytics. Students delve into topics such as econometrics, data visualization, and machine learning, providing them with comprehensive insights into how data can be leveraged to solve real-world economic problems. Additionally, the program emphasizes hands-on experience through practical projects and case studies, allowing learners to apply theoretical concepts in real scenarios.

Studying at the University of North Dakota offers an enriching experience in a country known for its diverse cultural landscape and strong academic tradition. Students benefit from a supportive learning environment, access to state-of-the-art facilities, and opportunities to collaborate with industry professionals, thereby enhancing their learning experience and employability in the global job market.

The skills gained from this program include critical thinking, advanced analytical capabilities, and a robust understanding of economic frameworks, making graduates well-equipped to tackle complex economic challenges.

Applicants for the M.S. in Applied Economics and Predictive Analytics typically need a bachelor's degree from an accredited institution. A strong background in economics, mathematics, or a related field is advantageous. Additionally, experience in data analysis or coursework in statistics and econometrics may be beneficial.

International students must demonstrate proficiency in English, generally through standardized tests like IELTS or TOEFL. A typical IELTS score of 6.5 or a TOEFL score of 90 is often expected, though exact requirements should be confirmed directly with the university.

International applicants will need to obtain a student visa to study in the destination country. This process typically requires valid documentation, including an acceptance letter from the university, proof of English proficiency, and financial statements. For detailed and specific visa requirements, prospective students should refer to official governmental pages or the international student office of the university.

• Data Analyst
• Economist
• Business Intelligence Consultant
• Market Research Analyst
• Policy Advisor
• Financial Analyst