April 06, 2026 03:24 pm (IST)
Follow us:
facebook-white sharing button
twitter-white sharing button
instagram-white sharing button
youtube-white sharing button
‘Not denied a ticket’: Annamalai explains absence from BJP’s Tamil Nadu candidate list | ‘Ghar-wapsi soon’: PoK wants to return to India, claims Imam organisation chief | Kerala polls shocker: Tharoor’s convoy stopped, security guard attacked mid-campaign | AAP drops Raghav Chadha from key parliamentary role, sparks buzz over internal rift | Amit Shah to camp in West Bengal for 15 days during Assembly polls; predicts Mamata’s defeat in state and Bhabanipur | 'BJP plotting President’s Rule, don’t fall in the trap': Mamata Banerjee on Malda unrest, urges peace | 'Most polarised state': CJI Kant raps Bengal govt over 9-hour hostage of judicial officers | Bengal SIR protest: Judge pleads for help amid mob attack after 9-hour hostage ordeal | Bengal SIR progress: 47 lakh of 60 lakh adjudicated cases disposed of, Supreme Court informed | Amit Shah to join Suvendu Adhikari on Bhabanipur nomination day; BJP plans mega roadshow
SKUAST-K  

Jammu and Kashmir:  National hands-on training on machine learning commences at SKUAST-K  

| @indiablooms | Dec 18, 2020, at 09:37 pm

Srinagar: A three-week national hands-on training programme on Machine Learning Technology commenced atSher-e-Kashmir University of Agricultural Sciences and Technology, (SKUAST) Kashmir with an aim toprepare human capital for the tech-driven job market and new-age agripreneurship. 

According to a statement, the online training programme has been organised by World Bank-ICARfunded National Agricultural Higher Education Project (NAHEP) for institutional development of SKUASTK in collaboration with varsity’s Agromet Division.

About 47 participants from across the countryincluding students, scholars and faculty from various agricultural universities of the country are takingpart in the three-week ‘Hands-on Training on Machine Learning: A Practical Approach’.

Vice-Chancellor, SKUAST-K, Prof Mushtaq Ahmad; Director, Planning and PI NAHEP, Prof Nazir AhmadGanai; Nodal Officer Agromet Division and course director, Dr Sameera Qayoom, HRM Consultant ProfFA Zaki and various heads, faculty members and students attended the inaugural session.

Theprogramme is being coordinated by the IDP-NAHEP team of the SKUAST-K.While speaking at the inaugural function of the programme, Prof Ganai said SKUAST-K has paced up theactivities for the transformation of agri-education and linking education with future technologies,innovation, entrepreneurship and the new-age job market.

“In order to compete and be at par with the 4th Gen industrial revolution, SKUAST K under the ambit ofNAHEP is working with top national, international institutes and tech companies to infuse the innovativeand tech-driven startup culture among students,” he said.Sameera Qayoom, in her address said, Machine Learning techniques are playing a vital role in everysector, including agriculture these days.

“The implementation of AI&ML enable agriculturists to accessincreasingly sophisticated data and provide analytics tools, which help them in efficient and effectivedecision making for better yield and quality crop production, she said.

Prof Zaki, at the occasion, said given the rising demand for food, automation of agriculture is the mainconcern as the traditional farming methods are not sufficient to fulfil the requirements, so there is aninherent and indispensable need for use of artificial intelligence in agriculture and allied sectors.

Various national and international experts on AI&ML are delivering the training which aims to teachstudents the fundamentals of AI&ML and its real-time applicability in agriculture including dataprocessing and analytics.

Support Our Journalism

We cannot do without you.. your contribution supports unbiased journalism

IBNS is not driven by any ism- not wokeism, not racism, not skewed secularism, not hyper right-wing or left liberal ideals, nor by any hardline religious beliefs or hyper nationalism. We want to serve you good old objective news, as they are. We do not judge or preach. We let people decide for themselves. We only try to present factual and well-sourced news.

Support objective journalism for a small contribution.