What are the software development tools? Software development includes application system development, embedded system software development, industrial software development, and software development for digitally intelligent series associated with large data artificial intelligence。
Several directions of software development learning, software development process
1. Application development
Applications, such as online malls, logistics management systems, office automation systems, etc., have been developed, bringing substantial benefits to society and increasing the income of programmers. They require skills such as the technological ecology of java's big data, the technological ecology of php, mobile phone android, the technological ecology of iphone, etc。
2. Embedded system software development
The basics of computer composition, operating system principles, c-programming, software engineering, etc., need to be put in place before developing embedded software, which means that the “computer science and technology” profession has advantages. An entry point for embedding can start with c-language programming, 51 series single-formula machines (the introduction does not need to select arm series because there are many arm repositories, many commands, many tube feet, which cause unnecessary trouble for you, but the design is very different, and 51 series still has a large market at the lower and middle end), then go to the market and buy 51 chips and imitation software for practice, and 51 chips are cheap。
3. Industrial software development
The advantages of mechanical and electronics studies are, of course, the advantages of mechanical and electronics, the inadequacy of software development courses in less than many mechanical and electronics colleges in the united states, such as the absence of a data structure and algorithm course, which is one of the core courses in industrial software, or the suggestion that students in the relevant professions should have a dual degree in “computer science and technology” or “software engineering”. Learning industrial software development requires mastering c-language programming, mastering the 51 series, the arm series and its compilation languages, simulation tools, using python instead of matlab when modelling is not available; then basic subjects, such as mathematics, mechanical design, electronics and their processes, public transport, data structure and algorithms, mathematical modelling, especially the subjects of probability and mathematical statistics, are essential. The development of industrial software is directly related to the upgrading of manufacturing industries, and if industrial software is subject to human control, manufacturing power countries can easily become empty words。
4. Software development for large data type applications
The large plant, represented by bat, has a number of large data applications in the country, such as scattered maps analysing the geographical distribution of the non-symptomatic patients of the new coronary virus in the big medical data, which has created opportunities for the development of large data applications, and has brought about benefits such as high salaries for the developers involved. This type of application development requires familiarization with big data applications such as the java technology ecoosphere,hadoop, spark, and python, which are well publicized by various media, and which can be used for a wide range of key words, such as data, and hasoop, not to mention here。
How about software development
5. Artificial intelligence software development
There are many cross-cutting disciplines in the development of artificial intelligence software, but the core cross-cutting disciplines are mathematics + computer science, and disciplines such as mechanical, physical, etc. Are actually supporting cross-cutting disciplines, although industrial robots still need some mechanically manufactured and electronic technology, but their brains are also mathematically associated “mechanical learning algorithms”, so how do they operate quickly? Of course, systems software such as computer chips, real-time operating systems, etc. Are required。
Remember that good artificial intelligence must be based on mathematics, better on a double degree in mathematics, and better on the computer base, that beginners can't equate python with artificial intelligence, that after matlab has been banned, python acts as a mathematical model, but that modelling algorithms do not require our own programming. All we have to do is focus on the algorithm “mechanical learning” of artificial intelligence brain operation itself. The higher level of development of artificial intelligence software is the development of a machine learning algorithm to enrich the skyarn algorithm in python. We need our own original algorithms of enhanced learning, rule-based learning, non-supervisory learning, or innovation based on other algorithms, not just a “shifter” or “participant”, of course, starting with them, otherwise we will not know the shortcomings of the current algorithm。
