Available courses

Information Systems- Analysis, Design, implementation, and management of a computer-based information system that support a wide spectrum of key policy and investment priorities for effective Agriculture. Agricultural Knowledge Management – Basic concept of Agricultural Knowledge & Knowledge Management system(KMS) life cycle, exploration of tacit knowledge creation and capture, codification of knowledge and implementing systems to make use of knowledge base, technical aspects of Knowledge Management in Agriculture – Business Intelligence and Data Analytics techniques – data mining, Knowledge-based/ Expert systems, Machine learning, fuzzy-logic, data visualization, content management systems and Web 2.0 technologies.

Laboratory Practical: Hands–on productivity software Applications- Word processing, Database, Spreadsheet, presentation & Graphics software, GIS mapping Software, OLAP (on-line Analytical Processing), use of statistical
packages e.g. SAS /SPSS, Matlab software tool boxes e.g. Bioinformatics, fuzzy-logic etc


Equip students with sound knowledge of the theoretical foundations of statistical estimation and decision analyses. Build students’ practical skills in the design and implement statistical inquiry, including data analysis, statistical estimation, hypothesis testing and interpretation of results.

The module is  designed  to  be  an  upper-level in agricultural microeconomic  theory  to  deepen  student  knowledge  in topics  such  as consumer  and  producer  theory, game  theory, labor and  capital  markets, externalities, and  public  goods. The course is more algebra intensive than  an introductory-level microeconomics  courses.