PGD in Statistical Methods & Analytics Course Syllabus

  • Years 1 Years
  • Type Course Post Graduate
  • stream Computer Science and IT
  • Delivery Mode
The syllabus for PGD in Statistical Methods & Analytics includes statistics, data analysis, probability, machine learning, and practical projects.

Syllabus & Subject: PGD in Statistical Methods & Analytics Course  

The syllabus for the PGD in Statistical Methods & Analytics course is designed to provide students with a comprehensive understanding of statistical concepts and data analysis techniques. The program typically covers foundational topics in mathematics and statistics, including probability theory, hypothesis testing, regression analysis, and multivariate analysis. Students also delve into data manipulation and visualization using software tools like R and Python. Advanced coursework often includes time series analysis, machine learning, and data mining, enabling students to handle complex data sets and make data-driven decisions. Additionally, the curriculum may incorporate practical projects and real-world case studies to apply statistical methods in various industries, preparing graduates for careers in data analysis, business intelligence, and research. Overall, the syllabus equips students with the skills and knowledge necessary to excel in the dynamic field of statistical methods and analytics.

S.NoSubjects
1Agricultural Farm Management
2Climate Change: Agriculture and Food Security                                                                       
3Basic Probability and Statistical Methods
4Rural Sociology
5Computer Operation & Programming
6Data Analytics and Experimental Design
7Agricultural Economics and Ag. Marketing
8Natural Resource Management
9Database Management & Business Analytics

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