Program Overview
With the rise of data science and its successful applications in various fields, there is an increasing interest from both the public and private sectors to explore the insights these methods can offer in economics, econometrics, and finance. Government and private sectors are interested in how data science techniques can inform the formulation and evaluation of policies. This program provides comprehensive training in using data science methods to analyze economic issues, covering theories, methods, and practical applications to real-world problems. It is designed to prepare students for careers as economic data analysts in government, central banks, or the private sector.
Program Objectives
The primary objective of the undergraduate program of BS in Economics with Data Science is to produce graduates who are proficient in both economic analysis and data-driven decision-making. Specifically, the program aims to provide students with a strong foundation in economic theory and econometrics with practical skills in data collection, analysis, and visualization using state-of-the-art tools and techniques using real-world applications of economic and data science principles.
The Program aims to:
- Use the modern data analysis techniques to study the economic relationships.
- Explore the critical issues in processing information to create data sets for statistical analysis.
- Equip students with the skills needed to apply data science methods to contribute to the formulation and evaluation of economic policy.
Upon completion of the degree, the students will be able to:
- Analyze economic and policy problems using in-depth knowledge of economic theory.
- Critically assess and engage with empirical economic research.
- Determine whether specific economic problems can be investigated empirically and devise appropriate strategies for such investigations.
- Explain the features, assumptions, and estimation methods used in econometric and data science methodologies.
- Design, develop, and conduct research on empirical economic issues using statistical and data science techniques and software.
- Analyze real-life data to understand and describe empirical issues across a range of disciplines and real-world settings.
Learning outcomes
Foundational Knowledge: Demonstrate a comprehensive understanding of fundamental economic principles, theories, and concepts and to acquire a solid grounding in statistical methods, probability theory, and mathematical techniques relevant to data analysis.
Data Analysis Skills: Develop proficiency in collecting, cleaning, and preprocessing data from various sources. Apply statistical techniques and econometric methods to analyze and interpret economic data. Utilize programming languages such as Python, R, or SQL to manipulate and analyze large datasets. Construct and interpret economic models to analyze relationships between variables and predict outcomes.
Data Visualization and Communication: Create visually appealing and informative data visualizations to communicate complex economic concepts and insights effectively. Develop the ability to present findings and recommendations to diverse stakeholders in a clear and persuasive manner, both orally and in writing.
Machine Learning and Predictive Analysis: Gain exposure to machine learning algorithms and techniques for predictive modeling and pattern recognition.
Interdisciplinary Integration: Integrate concepts and methodologies from economics and data science to address real-world problems and interdisciplinary challenges. Apply critical thinking and problem-solving skills to identify innovative solutions at the intersection of economics and data science.
Entry Requirements
The minimum eligibility criteria for admission in BS Economics is:
- Intermediate or equivalent with a minimum 50% marks from an accredited institution.
- Valid NTS test score as per CUI policy.
Duration
- Minimum: 8 Semesters; 4 years
- Maximum: 12 Semesters; 6 years
Credit Hours
Offering Semesters:
Eligibility Criteria
Scheme of Studies
Contact Details
Dr. Nuzhat Falki
Incharge Undergraduate Program
Email: nuzhat_falki@comsats.edu.pk
Mr. Fida Hussain
Senior Admin Assistant
Student Coordinator of MS Program & Ph.D
Email: fida_hussain@comsats.edu.pk