Internshala’s latest report highlights a 7.2x rise in women enrolment for online training programs
The report showcased that among many reasons, 49% of the women learners stated that the top reason they opted for online training was to gain an employment opportunity either an internship or a job. Whereas, 32% of women stated that they took up online courses to gain new skills. Other reasons attributed to women enrolling in online training programs were earning a certificate (8%), building a project (6%), and fulfilling college requirements(4%).
Also Read: Launch of Internshala Career Scholarship for Girls (ICSG) - 2023
Sarvesh Agrawal, Founder, and CEO of Internshala, said, “Time and again, it has been proven that education is the key to women empowerment, and I am a firm believer of this too. On the occasion of International Women's Day, we wanted to celebrate with this report on how women are opting for e-learning for their skilling and career-building requirements. The trends in this report demonstrate how women are trusting e-learning more and more over the years to supplement their education and strengthen their careers."
Also Read: Internshala Trainings launches ‘Skill Development Scholarship’, aims at skilling over 1 lakh students
He added further, "One trend especially stood out to me that 41% of women from tier-3 cities are trusting e-learning to skill up and build their careers. We at Internshala Trainings are extremely elated to learn that women in these cities are finding learning through online courses affordable and fruitful."
Also Read: Internshala launches Career Scholarship for Girls
Furthermore, as per the report, women have shown immense interest in STEM and management courses in the past year. Courses like online Web development, Digital marketing, and Python were among the top courses preferred by women in the year 2022 with a percentage of 29%, 19%, and 16% respectively. Women also actively pursued training in hot in-demand skills of today, like Advanced Excel, Financial Modelling and Evaluation, Data Science, and Machine Learning.