December 23, 2024 07:11 am (IST)
Follow us:
facebook-white sharing button
twitter-white sharing button
instagram-white sharing button
youtube-white sharing button
Mohali building collapse: Death toll rises to 2, many feared trapped for 17 hours | 4-year-old killed after speeding car driven by a teen hits him in Mumbai | PM Modi attends opening ceremony of Arabian Gulf Cup in Kuwait | Jaipur gas tanker crash: Toll touches 14, 30 critical | Arrest warrant against former cricketer Robin Uthappa over 'PF fraud' | PM Modi emplanes for a visit to Kuwait | German Christmas market car attack leaves 2 dead, Saudi Arabian doctor arrested | India, France come together to build world's largest museum in Delhi's Raisina Hill | Canada, US presented no evidence of Indians' involvement in purported criminal acts: Centre informs Parliament amid 'serious allegations' | Delhi Police Crime Branch to investigate FIR against Rahul Gandhi over Parliament tussle
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.