| Course Catalogue |
|---|
| Year | Semester | Courses | Key Learning Themes |
|---|---|---|---|
| Year I | Semester I |
• Logic and Critical Thinking • General Physics • Communicative English Skills • Geography of Ethiopia and the Horn • Mathematics for Natural Sciences • General Psychology • Moral and Civic Education • Physical Fitness |
Integration of communication, critical thinking, and foundational sciences and understanding historical and social concepts. |
| Semester II |
• General Biology • Social Anthropology • History of Ethiopia and the Horn • Economics • English Writing Skills • General Chemistry • Introduction to Emerging Technologies |
Advancement of communication and scientific literacy while promoting social awareness and ethical responsibility. | |
| Year II | Semester I |
• Calculus I • Linear Algebra I • Introduction to Computer Science and Application • Basic Statistics • Microeconomics • Inclusiveness |
Develop analytical problem-solving skills, computational thinking, and promote equitable participation and respect for diversity. |
| Semester II |
• Fundamentals of Programming • Calculus for Statistics • Linear Algebra II • Statistical Methods • Global Trends • Introduction to Probability Theory |
Building skills in applying calculus to statistical models, advancing knowledge of linear algebra, developing programming abilities, using statistical methods for inference, understanding global societal trends, and quantifying uncertainty through probability. | |
| Year III | Semester I |
• Sampling Theory • Regression and Econometric Analysis • Fundamentals of Database Systems • Statistical Computing I • Numerical Methods for Statistics • Macroeconomics |
Develop the ability to design representative samples, analyze variable relationships with econometrics, manage and query data using database systems, apply computational tools and numerical techniques for statistical problem solving, and understand overall economic performance and policy at the macro level. |
| Semester II |
• Statistical Computing II • Research Method and Sample Survey Practice • Design and Analysis of Experiments • Categorical Data Analysis • Time Series Analysis |
Strengthen skills in advanced data programming and visualization, applying research methods in real survey settings, designing and analyzing controlled experiments, modeling categorical data relationships, and analyzing patterns and forecasts in time-dependent data. | |
| Year IV | Semester I |
• Statistical Theory of Distributions • Demography • Statistical Computing III • Statistical Quality Control • Elective • Project I: Proposal Writing • Practical Attachment |
Focus on understanding probability distributions and their properties, analyzing population dynamics, applying advanced statistical computing with Python, machine learning, and AI, monitoring and improving process quality, and developing practical research and professional skills through proposal writing and field attachment. |
| Semester II |
• Statistical Inference • Biostatistics and Epidemiology • Project II: Research Project in Statistics • Introduction to Multivariate Methods • Elective • Entrepreneurship • Social and Economic Statistics |
Develop skills in drawing conclusions from data through statistical inference, applying biostatistics and epidemiology methods to health data, analyzing multiple variables simultaneously, understanding social and economic data patterns, fostering entrepreneurial thinking, and conducting a comprehensive research project in statistics. |