Machine vision is a multidisciplinary field that combines theory and practical expertise. When we learn software and programs, we must pay more attention to the combination of theory and hardware, theory and practice.
Both individuals and training institutions are emphasizing the importance of high-level languages and machine vision software. In fact, the biggest task of training institutions is to increase employment opportunities for students. It is absolutely impossible to be high-tech, but there is more knowledge system than novices, and the salary is also middle and lower levels. Most employers like students who have been trained and have a certain foundation. The employer also saves a lot of training costs.
Summary Most people, no matter what the purpose of their training. No training is better than training. However, there is too much emphasis on the importance of software and neglect of hardware assembly, familiarity, and use. Many people cannot understand even the most basic wiring diagram. The lack of knowledge system is shocking and unacceptable to employers. Many people cannot drive screws, let alone open threads. Enterprises and units are so scared that they can only observe in isolation and wait until the performance of the project to determine whether they can lead the project independently. But often trained students can develop projects independently faster.
I can learn a sentence from your interview. It’s because of your low technical level. Of course, we must have the most basic operations and understanding. No one is perfect. What the employer hopes most is that you will not cause problems, but solve them and promote the employer's on-site projects. Rather than a word from you, I can learn. The company thinks you've finished your studies and run away.
So I think an excellent training institution is like this: expandable employment opportunities, expandable knowledge system, paying more attention to the actual results of students, and more importantly, continuous assessment.