Candidates: 139 | Batches: 14 | Employers: 3019149 | Wage Employement: 0 | Self Employed: 0 | ____ *System USP* ____ • Six Level Entry System for Stakeholders. • Inter Alia Visibility of All Stakeholder on Real Time Basis. • Geo Level Mapping of All Stake Holders. • Realtime Monitoring of Entire Skill Process. • Mass Level Communication. • Complete Platform for Execution of Government Skill Programs. • Scope For Customisation of Schemes. • Only Platform Meeting All Requirements of CSR And Other Funds. • Data Security. ____ | ____ *Benefits to Candidates* ____ • Livelihood Driven Certified Training Continuous Career Counselling. • Update on Up-Skilling & Advance Skilling Programmes. • Certification as Per Global Standards. • Introduction to Special Category Benefits. • EDP- Entrepreneurship Development Programme. • Option to Work Part Time/Work from Home. • Connect to Global E-Commerce Platform. • Induction to All Social, Economic & Govt. Benefits. ____ | ____ *Benefits to Employers* ____ • Employer Orientation & Training. • Facilitates Multisectoral Registration of Employers. • Facility for Multiskilling, Cross Sectoral Skilling Based Work Order. • Meets Regulatory Compliance. • Inbuilt Policies to Avoid Conflicts. • Inbuilt Two-Way Bidding System. • Facilities to Accommodate Unskilled Manpower. • Employer-Employee Feedback & Rating Mechanism. • Inbuilt Employer Assessment. ____ | ____ *Benefits to Training Providers* ____ • Work Order/Employment Based Training. • Facilitates Multiskilling & Cross Sectoral Skilling. • Facilitates Existing as well as New Customized Schemes . • Ensures Optimum Utilization of Resources. • Facilitates On-line/Off-line Training of Candidates. ____ | ____ *Benefits to Govt. / Economy* ____ • Generation of 1 Million Livelihoods in Noida. • 70%- Industrial Employment, 30%-Self Employment . • 50 % Livelihood Opportunities for Women. • 70 % Beneficiaries from Neighbouring 15 Districts in U.P.. • Increased Per Capita Income-Improved Standard of Living . • Boost to GDP through Employment-Led Growth. • Skilled Workforce to Attract More Investment from Business . • Reduction in Workforce Migration from the Region. ____ | ____

Candidates Details

S.No Candidate Id Candidate Name State Job Role Gender
101 118382DMN Sunita Uttar Pradesh Sewing Machine Operator(AMH/Q0301) Female
102 008382DMM Anita Uttar Pradesh Sewing Machine Operator(AMH/Q0301) Female
103 468382DMN Sunita Uttar Pradesh Sewing Machine Operator(AMH/Q0301) Female
104 468382DMM Ankita Uttar Pradesh Sewing Machine Operator(AMH/Q0301) Female
105 008382DMMM Manisha Uttar Pradesh Sewing Machine Operator(AMH/Q0301) Female
106 2025KS-X7BTCNSF1326 Priya Singh UP Sewing Machine Operator(AMH/Q0301) Female
107 2025KS-EJ7PKQQT1328 Kavita Yadav UP Sewing Machine Operator(AMH/Q0301) Female
108 2025KS-LVDWJOUN1325 Ramesh Kumar Rajasthan Sewing Machine Operator(AMH/Q0301) Male
109 2025KS-GIOOOGWX1329 Arjun Meena Rajasthan Sewing Machine Operator(AMH/Q0301) Male
110 2025KS-NLC4ZFGH1327 Anil Verma MP Sewing Machine Operator(AMH/Q0301) Male
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