Insurance Research Shortcut: How to Prepare for Cross-Insurance? In-depth dismantling of interdisciplinary insurance research.
If you are going to cross insurance, you are not satisfied with the major, or even if you are not satisfied with the major ranking, I suggest you consider cross-insurance. The logic of cross-insurance and cross-examination are different, cross-examination needs to dig very deep information, but cross-insurance you need to first determine the positioning, and then according to the cross-major you position, to determine the correlation between your cross-major and the current major.
And most people are often blindly preparing for cross-insurance. Most people think that cross-insurance is only the right of the top few majors, and most people think that cross-insurance must have a minor double degree to be comfortable, these are actually you comforting yourself.
If you study statistics in this major, the knowledge you have learned is actually applied in more than one or two disciplines. You can consider cross-insurance new biography category; You can also consider quantitative finance and financial technology in cross-insurance finance; You can also completely follow the major, the master's degree in statistics, the master's degree in applied statistics, or you can completely abandon the major.
Consider economics academics, all kinds of choices, all of which mean that you have to prepare for different experiences in college, to convince the corresponding teachers, you have the corresponding qualifications and energy, to complete the study of different majors of graduate school. Most people are mispositioned in the first step, or most people are eager to satisfy their anxiety through heap competitions and research internships.
If you really want to cross insurance, sophomore year is a very good time node to determine the key time node of the project you want to cross-insurance, and when you finally go to insurance research, offline summer camp situation, dozens of projects may be put out a day, and you don't have time to engage in so much investment at this time.
Of course, I recommend that everyone invest in Haitou, but Haitou should also have a strategic focus, which projects you want to invest in, not all projects but you can invest in.
If your undergraduate science is automated, I will say the first-level discipline corresponding to this major: control science and engineering. There are so many subdivisions below like pattern recognition, artificial intelligence, robotics engineering, traditional control navigation, guidance and control, instrument schedules messy these directions. Some people like the hardware to do in the direction of embedded, and embedded engineers do embedded related research. Which direction do you want to choose? It's you who make sure in the second semester of your sophomore year.
→ when you investigate clearly based on this specialty, you can probably cross the direction of insurance before you can determine it. What experience you have to make up next, which can maximize your final delivery probability is a little higher.
→ you do a few games in general, do a little bit of software, do a little of hardware, do you end up keeping soft or hard? The software teacher will think that you go to ensure the hardware, and the hardware teacher will think that you go to ensure the software.
This is also why many juniors have taken sea pitches when they submit this year, and so far each tutor's reply to him is to be determined or welcome to apply for summer camp. Once you have identified your goals, it is time to deeply disassemble the correlation between your inter-discipline and your specialty.
→For example, if you want to cross big data, now the undergraduate science is economics, can you find a combination of big data and economics related to this kind of topic. For example, if you are currently studying pharmacy and want to reincarnate medical engineering, can you find a topic in the field of combination between medicine and biomedical engineering to do it? There is also a logic that is also practical.
→ if you move from a very hard subject to a relatively soft subject. For example, if you turn from computer to soft work, from computer to big data, from computer to finance, from a harder major to a softer discipline, in this case you don't need to do too many related things.
