Student learning

Postgraduate projects, practical work and internship experiences

The M.Sc. Agricultural Statistics programme began in 2014. The department has four PG seats and two PhD seats, with practical learning through computing, research projects and faculty guidance.

4PG first year
4PG second year
2PhD first year
3PhD second year

Internship applications

The department’s internship landing page provides current calls, eligibility, programme details and application instructions.

View internship applications →

Examples of student work

  • Black pepper knowledge delivery: an AI chatbot explored by Blesson B. Varghese under the guidance of Dr. Pratheesh P. Gopinath.
  • Pineapple price forecasting: comparison of time-series and machine-learning approaches in work presented by Arshida A. K.
  • Data visualization: grapesDraw, an R package developed by Burra Preeti.
  • Crop quality: a convolutional-neural-network approach to Nendran banana ripening classification.

Student learning includes work with R packages, computer vision and statistical applications. Contact the department for internships, supervision and application details.