To accelerate the cultivation of new skilled talent aligned with the demands of the digital economy and the intelligent era, and to promote the growth of emerging industries, a specialized training initiative was conducted from May 14th to June 1st.
The program, known as the "Taishan Smart Training" 人工智能 application project, successfully completed seven training sessions for the role of 人工智能 trainer.
A total of 283 trainees participated, with 253 successfully passing the assessment and obtaining certification, thereby becoming a new force for the development of the digital economy in the region.
This "Taishan Smart Training" project is one of two provincial-level key initiatives selected for the city.
It closely follows the requirements of broader training campaigns, effectively integrating the employment needs of key groups, such as new university graduates, with the skill demands of critical digital industries like data annotation.
The program innovatively implements a project-based training model that integrates job requirements, skill training, skill evaluation, and employment services.
It streamlines the process from public recruitment and small-class offline instruction to final assessments and targeted recruitment presentations, helping trainees master practical skills and facilitating high-quality employment, thereby creating a model for skills enhancement in the local digital economy sector.
To ensure the training effectiveness, the relevant authorities selected three local universities as the training institutions through an open and selective process.
These institutions assigned dedicated instructors with high academic qualifications and rich practical experience in the 人工智能 field to teach, employing a combined approach of theoretical and hands-on instruction.
The curriculum is closely aligned with industry frontiers in future and emerging sectors, covering not only the foundational knowledge and application principles of 人工智能 but also intensively focusing on practical skills urgently needed by the industry, such as data annotation, text processing, and image labeling, ensuring trainees can quickly get started, learn effectively, and apply their skills.
To strengthen the employment focus of the training and promote the goal of "employment upon graduation," the authorities linked the disbursement of training subsidies to the actual post-training employment rate of participants, encouraging the training institutions to enhance post-training employment services and guidance.
Following the training, multiple recruitment sessions were organized jointly by the authorities and the training institutions.
Twelve high-quality AI companies participated, offering positions directly to the trainees and conducting face-to-face discussions, achieving precise matching between talent and job opportunities.
Currently, 70 trainees have reached preliminary employment intentions with these companies, demonstrating a rapid conversion of training outcomes into tangible employment results.
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