Students who have participated in the recruitment of large companies, especially those who are recruited on campus, can easily find that many large companies like interview algorithms and data structures.
Before, I thought a little bit about this issue. Recently, a little Lei fan specifically asked this question. so, simply say a few words, and make fun of it.
1. First of all, I want to complain. This is definitely a direct manifestation of the pretense of a big company.
Through many tall algorithm and data structure questions, it reflects the difference between myself and other companies. Especially the ones that are particularly difficult, as soon as they leave the examination room, they become lively, and the Internet also becomes lively.
2. What type of topic has the most gold content, naturally it is the data structure and algorithm.
Only through the tall questions can we identify which are smart and diligent children and which are incompetent younger brothers.
You have to know that BAT and other companies pay fresh undergraduates with a salary of more than 10,000 a month, and probably more than 130,000 a year.
Salary, talent, and interview difficulty are naturally related.
3. Algorithms and data structures are the essence of program design.
Algorithm, I think it is a very pretending word. Public opinion in books and on the Internet has shaped the term taller.
I don't think so. Why, I like to put forward some new ideas.
Algorithms are nothing more than solutions to problems, what's so great.
Farmers, construction, medical care, which industry does not have a solution to the problem, only IT program design has developed an algorithm.
The solution to problems is the basic productivity of all industries and the basic means of work and production of labor.
It can be said that the world is made up of problems, and humans are solving problems every day.
4. The topics of algorithms and data structures are relatively standardized. Facilitate questioning and acceptance.
In a few words, the context of a question is clearly defined, and the candidates will answer individually.
Moreover, this topic is not easy to memorize by rote, and it can block many people such as "nerds".
5. The above complaint only speaks half of the problem. The other half is why there are so many big companies instead of small companies.
The business of a large company is more complicated, the technology used is more difficult, and the requirements for a person's ability and quality are very high. Big data, cloud computing, high performance and other requirements are also relatively large, and the requirements for basic skills such as data structure and algorithms are relatively high. The foundation of data structure and algorithm can show a person's growth potential.
Small and medium-sized companies are more concerned about short-term benefits and hire workers who can work immediately to help the company make money. What can make money right away, of course, is to do projects, not to do research. Algorithms and other things are not used at all. Small and medium-sized companies do more business systems and websites. Progress, performance, and business are the main ones, and algorithm requirements are very low.
To use an analogy, the algorithm is like the internal strength in martial arts. If you learn well, you can become a prawn and dominate the martial arts in the future. However, no matter how good your internal strength is, you can't perform without any moves. Doing projects and developing applications are just like the moves in martial arts. If you learn one-and-a-half moves, you can find soft persimmons to squeeze and experience the thrill of learning martial arts.
6. Whether it is an algorithm or a project, it is the actual demand of the market and should be learned and applied.
We just need to know that the market is the market and we are ours.
It should always be clear which direction you want to develop.
What to learn, how much, and how deep is the key to personal pursuit.
Don't be confused by the recruitment needs of companies in the market and the comparison of surrounding people and netizens.
7. Come out and mix, grab money with one hand, and ideal with the other.
Look at the algorithm and data structure and the so-called big company, whether it has anything to do with your banknotes and ideals.