New Delhi, Feb 13 : Nasscom Foundation on Thursday, in partnership with MathCo, launched a special skill development programme to train “neurodivergent” youth in data annotation.
Generally, a “neurodivergent” person refers to someone on the autism spectrum, whose brain processes information in a way that is not typical of most individuals.
The initiative aims to enhance employment opportunities for them in the growing field of artificial intelligence (AI) and machine learning (ML).
The programme will train 50 neurodivergent individuals with a focus on both technical and soft skills. The training will be conducted in two phases, with 25 participants in each batch.
Participants will not only learn data annotation, a crucial skill for AI models, but will also receive mentorship and confidence-building support to help them succeed in the workplace.
“We believe that a truly inclusive India begins with creating accessible and empowering environments,” said Jyoti Sharma, CEO, Nasscom Foundation.
“Learning is the first step toward empowerment, and continuous learning is key to staying ahead in an evolving world,” added Aditya Kumbakonam, COO and Cofounder, MathCo.
He added that these young individuals will not only make the most of this opportunity but will also continue to grow and adapt as they build their careers.
Nasscom Foundation will provide ongoing mentorship and conduct sensitisation sessions for employers to ensure a supportive environment for neurodivergent employees.
The goal is to place at least 60 per cent of participants in internships and jobs in the IT and IT-enabled services (ITES) sectors.
Data annotation, which involves labelling and tagging data to train AI models, is a skill in high demand as AI applications continue to grow across industries.
By equipping “neurodivergent” youth with this skill, the programme aims to open new career opportunities and foster a more inclusive workforce.
Recently, Nasscom Foundation, in partnership with NITI Aayog, said it is digitally empowering one lakh lives in India’s Aspirational Blocks. (With inputs from IANS)