Advertisement

Countermeasures for Training Computer High-Skilled Talents in the Era of Artificial Intelligence

  • Xinhao Sun
  • Yue HaoEmail author
Conference paper
  • 30 Downloads
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1146)

Abstract

With the rapid development of artificial intelligence, the competition between various computer enterprises is becoming increasingly fierce. In this fierce competition, talents will inevitably become the key factor for the survival and development of various enterprises. However, computer professionals vocational ability and enterprise’s expectations, but there is a certain gap between especially in computer skills training, often exist in understanding unclear demand trends to unit of choose and employ persons, unpredictable phenomenon, therefore, under the background of the rapid development of artificial intelligence computer lack of high-skilled talents reserves has become the hot topic of the whole society. In reaction to the phenomenon, this paper puts forward the innovative entrepreneurial, engineering education concept into the high-skilled talents cultivation in computer system, based on the analysis of computer training institutions and universities about the present situation of computer training, fully elaborated in this paper, the computer high-skilled personnel training target, training, strategy of the new theory, new points, will strive for applied talents cultivation idea is applied to the computer talents training, so as to get rid of computer high-skilled personnel training speed can’t keep up with development of artificial intelligence.

Keywords

Artificial intelligence Highly skilled personnel Cultivation strategy Professional ability 

References

  1. 1.
    Wu, W., Song, H.: On transformation of talent training of law undergraduates under the background of “internet+”. J. High. Educ. 628(108), 7–34 (2017)Google Scholar
  2. 2.
    Zhou, Y., Liu, Y., Wang, R.: Training deep neural networks for image applications with noisy labels by complementary learning. J. Comput. Res. Dev. 26(65), 528–539 (2017)Google Scholar
  3. 3.
    Turner, M.A.: The alacrity program: identifying, training, and growing the talent required to build profitable new information and communication technology companies in Canada and internationally. Can. Public Policy 4(6), 1–8 (2018)CrossRefGoogle Scholar
  4. 4.
    Fossum, S., Cunningham, C., Ristkari, T.: Does parental mental health moderate the effect of a telephone and internet-assisted remote parent training for disruptive 4-year-old children. Scand. J. Psychol. 59(2), 7–19 (2018)Google Scholar
  5. 5.
    Lawford, B.J., Hinman, R.S., Kasza, J.: Moderators of effects of internet-delivered exercise and pain coping skills training for people with knee osteoarthritis: exploratory analysis of the IMPACT randomized controlled trial. J. Med. Internet Res. 20(5), 100–121 (2018)CrossRefGoogle Scholar
  6. 6.
    Matongolo, A., Kasekende, F., Mafabi, S.: Employer branding and talent retention: perceptions of employees in higher education institutions in Uganda. Ind. Commercial Train. 50(2), 284–289 (2018)Google Scholar
  7. 7.
    Wu, W., Zhu, D., Fan, J.: On innovative talent training program for robot engineering. J. High. Educ. 773(1137), 1273–1285 (2017)Google Scholar
  8. 8.
    van de Ven, R.M., Murre, J.M.J., Buitenweg, J.I.V.: The influence of computer-based cognitive flexibility training on subjective cognitive well-being after stroke: a multi-center randomized controlled trial. PLoS ONE 12(11), 187–194 (2017)Google Scholar
  9. 9.
    Westergren, A., Edfors, E., Norberg, E.: Long-term effects of a computer-based nutritional training program for inpatient hospital care. J. Eval. Clin. Pract. 23(4), 6–12 (2017)CrossRefGoogle Scholar
  10. 10.
    Baumgart, D.C., Wende, I., Grittner, U.: Tablet computer enhanced training improves internal medicine exam performance. PLoS ONE 12(4), 5–6 (2017)CrossRefGoogle Scholar
  11. 11.
    Zhang, L., Chen, Y., Tan, X.: An improved self-training algorithm for classifying motor imagery electroencephalography in brain-computer interface. J. Med. Imaging Health Inf. 7(2), 330–337 (2017)CrossRefGoogle Scholar
  12. 12.
    Chen, H.-T., He, Y.-Z., Hsu, C.-C.: Computer-assisted yoga training system. Multimed. Tools Appl. 77(4), 1–23 (2018)Google Scholar
  13. 13.
    Li, Q., Huang, C., Lv, S.: An human-computer interactive augmented reality system for coronary artery diagnosis planning and training. J. Med. Syst. 41(10), 159 (2017)CrossRefGoogle Scholar
  14. 14.
    Stiller, K.D., Köster, A.: Learner attrition in an advanced vocational online training: the role of computer attitude, computer anxiety, and online learning experience. Nephron Clin. Pract. 19(2), 1–14 (2017)Google Scholar
  15. 15.
    Baker, K., LaValley, M.P., Brown, C.: Efficacy of computer-based telephone counseling on long-term adherence to strength training in elders with knee osteoarthritis: a randomized trial. Arthritis Care Res. 19(5), 278–293 (2019)Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.College of Business AdministrationJilin Engineering Normal UniversityChangchunChina

Personalised recommendations