Course Description
M.Sc. in Economics and Data Science program is an interdisciplinary graduate degree designed to equip students with advanced knowledge of economic theory and cutting-edge data science techniques. The program emphasizes integrating quantitative methods, programming skills, and analytical tools to address real-world economic and policy challenges. Graduates will be prepared for careers in academia, industry, or government, where they can leverage data-driven insights to inform decision-making and innovate in the digital economy.
As a flagship initiative of our university, this master’s program will serve as the cornerstone for establishing the Central Asia School of Economics (CASE), further solidifying our commitment to advancing economic research and policy analysis in Uzbekistan. CASE will be based on three pillars: MEDS, GEAR (The Greater Eurasia Research Center), and YESU (Young Economists Society of Uzbekistan) and we envision an emergence of vibrant and community of young economists, who will make a decisive contribution to the nation’s economic growth and prosperity.
Course Structure
The program consists of ECTS 120 credits distributed over two year full-time.
Semester 1 - Fall Semester
| Year One | ||
|---|---|---|
| Modules | Courses | ECTS |
| Module 1 | Microeconomics 1 | 3 |
| Probability theory and statistics | 3 | |
| Math for Economics | 3 | |
| English and critical thinking | 3 | |
| Module 2 | Microeconomics 2 | 3 |
| Microeconomics 1 | 3 | |
| Data analysis | 3 | |
| English and critical thinking | 3 | |
| Module 3 | Microeconomics 3 | 3 |
| Microeconomics 2 | 3 | |
| Econometrics 1 | 3 | |
| Data analysis | 3 | |
| Module 4 Track 1: Economic Theory |
Public finance 1 | 3 |
| Macroeconomics 3 | 3 | |
| Econometrics 2 | 3 | |
| Growth theory and economic policy | 3* | |
| Topics in Economics | 3* | |
| Module 4 Track 2: Applied Economics |
Public finance 1 | 3 |
| Macroeconomics 3 | 3 | |
| Econometrics 2 | 3 | |
| Applied policy analysis* | 3* | |
| Energy economics* | 3* | |
| Module 5 Track 1: Economic Theory |
Public finance 2 | 3 |
| Econometrics 3 | 3 | |
| Macroeconomics 4 | 3 | |
| Growth theory and economic policy* | 3* | |
| Topics in Economics* | 3* | |
| Module 5 Track 2: Applied Economics |
Public finance 2 | 3 |
| Econometrics 3 | 3 | |
| Macroeconomics 4 | 3 | |
| International trade* | 3* | |
| Development economics* | 3* | |
| Total credits for the year one | 60 | |
| Year two | ||
|---|---|---|
| Modules | Courses | ECTS |
| Module 6 Track 1: Economic Theory |
Research methods | 3 |
| Data analysis | 3 | |
| Principles of finance | 3 | |
| Algorithms and data structures | 3 | |
| Module 6 Track 2: Applied Economics |
Research methods | 3 |
| Data analysis | 3 | |
| Principles of finance | 3 | |
| Circular economy | 3 | |
| Module 7 Track 1: Economic Theory |
Research methods | 3 |
| Data analysis | 3 | |
| Industrial organization | 3 | |
| Algorithms and data structures | 3 | |
| Module 7 Track 2: Applied Economics |
Research methods | 3 |
| Data analysis | 3 | |
| Industrial organization | 3 | |
| Economic consultancy monitoring and evaluation | 3 | |
| Module 8 Track 1: Economic Theory |
Capstone project | 3 |
| Data analysis | 3 | |
| Industrial organization | 3 | |
| Advanced game theory | 3 | |
| Module 8 Track 2: Applied Economics |
Capstone project | 3 |
| Data analysis | 3 | |
| Industrial organization | 3 | |
| Agricultural and natural resource economics | 3 | |
| Module 9 Track 1: Economic Theory |
Capstone project | 3 |
| Industrial organization | 3 | |
| Advanced game theory | 3 | |
| Object oriented programming | 3 | |
| Module 9 Track 2: Applied Economics |
Capstone project | 3 |
| Data analysis | 3 | |
| Industrial organization | 3 | |
| Agricultural and natural resource economics | 3 | |
| Module 10 | Internship | 9 |
| Capstone project | 3 | |
| Total credits for the year two | 60 | |
Note: The structure of the course is subject to change.
Program learning outcomes
Graduates of the M.Sc. in Economics and Data Science will possess:
- • Advanced Economic Knowledge: Master economic theories, models, and methodologies to analyze complex issues.
- • Proficiency in Data Science Tools and Techniques: Evaluate policies and market trends, applying evidence-based solutions using Python, R, or similar for data analysis and computational modeling.
- • Research Competence: Conduct independent research and communicate findings effectively. Develop and apply advanced mathematical and statistical methods to analyze economic phenomena and large datasets. Conduct independent and collaborative research using cutting-edge methods in economics and data science.
- • Global Perspective: Analyze economic issues from a global and multicultural perspective.
- • Ethical Decision-Making: Address ethical considerations in economic analysis and policy.
- • Global Perspective: Analyze economic issues from a global and multicultural viewpoint.
- • Leadership and Communication: Demonstrate leadership, teamwork, and clear communication of economic concepts.
- • Lifelong Learning: Commit to continuous learning and adaptability in evolving economic contexts.
Program degree requirements
To graduate from the Master of Science in Economics and Data Science program, students must meet the following academic, research and administrative requirements
- 1. Academic coursework
Completion of required credits: successfully complete a total of 120 ECTS credits as defined by the curriculum. - 2. Capstone project: Master’s thesis
Conduct original research in economics and data science under faculty supervision. Submit a written thesis that meets academic standards and defend it successfully before a committee. The thesis should demonstrate the ability to apply data science methods to economic problems and contribute new insights to the field. - 3. Internship (Optional for Applied economics track)
Applied Economics track requires an internship at a relevant role. - 4. Attendance and participation
Meet the program’s attendance requirements, including participation in lectures, seminars, workshops, or other required academic activities.
Entry requirements
- • Bachelor degree from an accredited institution (minimum 180 ECTS credits) or a higher academic qualification (degree course format should be full-time or part-time)
- • A pass in Entrance Exam.
Applicants with a GRE/GMAT (10th or Focus edition) certificate may be exempt from the entrance exam. Their exam results will be based on their score in the GRE/GMAT Math (Quantitative) section.
To check how GRE/GMAT Math (Quantitative) score compares to the exam score, please use the equivalency table below.
If applicants prefer, they may still take the exam. In case of a difference between the score granted from the GRE/GMAT Math (Quantitative) section and the exam score, the higher score will be considered.
Equivalency table
| GMAT 10th Edition | |
|---|---|
| GMAT Score |
Entrance Exam Score (in percentage) |
| 50-51 | 100 |
| 48-49 | 95 |
| 46-47 | 90 |
| 44-45 | 85 |
| 42-43 | 80 |
| 40-41 | 75 |
| 38-39 | 70 |
| 36-37 | 65 |
| 34-35 | 60 |
| 32-33 | 55 |
| 30-31 | 50 |
| 28-29 | 45 |
| GMAT Focus Edition | |
|---|---|
| GMAT Score |
Entrance Exam Score (in percentage) |
| 89-90 | 100 |
| 87-88 | 95 |
| 85-86 | 90 |
| 83-84 | 85 |
| 81-82 | 80 |
| 79-80 | 75 |
| 77-78 | 70 |
| 75-76 | 65 |
| 73-74 | 60 |
| 71-72 | 55 |
| 69-70 | 50 |
| 67-68 | 45 |
| GRE | |
|---|---|
| GMAT Score |
Entrance Exam Score (in percentage) |
| 169-170 | 100 |
| 167-168 | 95 |
| 165-166 | 90 |
| 163-164 | 85 |
| 161-162 | 80 |
| 159-160 | 75 |
| 157-158 | 70 |
| 155-156 | 65 |
| 153-154 | 60 |
| 151-152 | 55 |
| 149-150 | 50 |
| 147-148 | 45 |
English language requirements
Proficiency in the English language as evidenced by one of the below:
- • IELTS 6.0 or higher
- • TOEFL iBT 60 or higher
Note: We accept only the TOEFL iBT taken at approved test centers. We do not accept the TOEFL iBT Home Edition.
- • CEFR B2
Applicants who have completed their bachelor’s degree entirely in English do not need to provide any additional proof of language proficiency.
Exam Date and Deadline for Registration
| Exam Date | Deadline for Registration |
|---|---|
| 26th April | 18th April |
| 14th June | 6th June |
| 23rd August | 15th August |
Fees and Funding
| Tuition Fee for 2025/2026 Academic Year | |
|---|---|
| Local students | 27 500 000 UZS per academic year |
| International students | $ 3,250 USD per academic year |
Career Perspectives
M.Sc. in Economics and Data Science program emphasizes integrating quantitative methods, programming skills, and analytical tools to address real-world economic and policy challenges. Graduates will be prepared for careers in academia, industry, or government, where they can leverage data-driven insights to inform decision-making and innovate in the digital economy.
